JasonCEC

Just as a PSA - I develop food and beverage products (both premium and mass market) with Analytical Flavor Systems (a predictive platform for flavor);

no one in the industry - not a single person who knows anything about coffee - would recommend civet coffee. Its a marketing gimmick of the worst kind. Its destructive, a-historical, and does not result in a better product.

Any random "3rd wave" coffee is better, and if you want a fruity-fermented profile, just look for a "natural process" or "honey processed" coffee.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist

Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A company.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist

Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A company.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/

Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist

Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A company.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Does anyone have suggestions for an Android based alternative to Google Maps? (preferably open source, etc)

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A startup. Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A startup.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist

Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A startup.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/

Positions: Full-Stack Engineer, Data Scientists, R&D Product Formulator / Scientist

Overview: Gastrograph AI is an artificial intelligence platform for modeling human sensory perception of flavor, aroma, and texture to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products, enter new markets, and optimize their existing brands. We're a diverse 12 person post Series-A startup.

Application & Data Stack: Javascript, React & React Native, Java, GraphQL, Spark, R, postgres/MySQL, AWS

The Position(s)

_Data Science_: We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. Our Data Science team develops new models and algorithms from scratch to make second-order inference on sparse data sets from non-representative samples that generalizes to the underlying target population. We rely on cutting edge models such as persistent homology, PU Learning, and metric learning to make predictions on non-eucldian human sensory data. We don't use tensor flow or pandas or keras as they are not a good fit for our problem space. We prefer a deep understanding of math and stats VS experience running logistic regressions in Python. (but we're cool with Python / Logit / experience)

_Engineering_: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Data-Engineers with experiance in micro-batch processing for machine learning pipelines.

Next Steps: please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

This is our technical interview for data science interns (and full time data scientists, without the deadlines!);

Lots of us here (rightfully) complain about the interview process, coding tests, white board interviews, and projects - your feedback won't fix that across the industry, but would help us improve the process we are actively using to hire data scientists at Analytical Flavor Systems.

Any constructive feedback is greatly appreciated.

It is, to a large extent, rather unbelievable to watch otherwise respectable individuals fall over themselves to promote valueless and literally "worthless" cryptocurrencies. I have trouble reading in good faith about the lack of SEC action being anything other than a warning sign, and the new "test" having any legal standing as a defensible position.

In all, this is rather sad. I've pitched USV before, I've read AVC for years, and I've found then to be among the more thoughtful of investors.

Given their recent decsent into madness - I wouldn't touch them with a 10ft pole.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster. Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Hey Everyone... CEO of AFS here. Happy to answer questions as they come up.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems may be able to help. Contact info in profile.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS

Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

Analytical Flavor Systems | Manhattan - NYC | Full-Time | Onsite | http://www.Gastrograph.com/ Position: Full-Stack Engineer, Application Engineer, DevOps, Data Scientist

Application & Data Stack: Javascript, React & React Native, GraphQL, Docker, Spark, R, postgres/MySQL, AWS

Team: we're a diverse 6 person company (across Data, Engineering, Chemistry, and Biz). Everyone gets trained as a professional taster.

Gastrograph AI is an artificial intelligence platform for modeling human sensory perception to predict consumer preferences of food & beverage products. We help food and beverage companies develop new products and optimize their existing brands by predicting the optimal flavor, aroma and texture for target consumer cohorts.

Our Services

_Innovation Management_: New product development, flavor profile optimization, & portfolio management (multi-product optimization).

_Cognitive Marketing_: Product description optimization to prime consumers to like a product more by purposely engineering a perception bias.

_Deep Market Insights_: Predictions for emergent market preferences by region and demographic.

The Position(s)

_Engineering_: We're currently looking in two specific areas: (1) full stack engineers with experience with React, GraphQL, and React Native to work on our web app for clients and our mobile app for tasters. (2) Streaming infrastructure focused engineers capable of integrating the data pipeline and outputs of machine learning models into an easy to use management platform.

_Data Science_: Data science is central to the value and insights we provide for our clients. We didn't build a data science team to optimize our product's marketing spend, sales funnel, or client retention – we built a data science team to build our product. We are a team of data scientists that understand our clients and turn nebulous business goal into quantitative decision metrics and predictive models to optimize those metrics. The extensive role of data scientists at Analytical Flavor Systems allows us to invest in their education across sensory perception (standard sensory science so they know what we're improving and replacing), tasting experiences (so they appreciate the products we work on and understand how the data is collected), production knowledge, and data science tear-downs (a meeting where the team collaboratively attempts to find and fix problems, try new techniques, and debate the philosophical implications of a model's construction).

Next Steps

Please contact Jason Cohen at JasonCEO@Gastrograph.com to apply.

I see as many adults addicted to their phones and social media as high-school aged students. With new technology like this, its not surprising some people may need help coping with applications designed to be addictive.

I found the article quite poignant and well written. I think a class like this would do most people well, and could break individuals out of the social-media surface-level dopamine cycle that drives them into an unhappy addiction.

Hello HN. I'm Jason, the CEO of AFS.

Happy to answer any questions!

That is correct.

The link to the meetup group is here:

https://www.meetup.com/Hacker-News-NYC

Hello everyone!

I'm a co-organizer on the new HN NYC meetup; we're open to suggestions and would be happy to integrate ideas! let's discuss in this thread?

Cheers! - j

The psychological effect is "tendency towards the mean", and in this case, the mid-point isn't the mean.

Forcing individuals to choose a score above or below the mean yields a better sampling of the true distribution in this case.

There is actually a whole theory around this, and has lots of implications for the designs of hedonic and sensory scales.

I work on modeling human sensory perception and preference of food and beverage products, and have had to design scales that work as a true "metric";

Most scales suffer from 3 primary problems:

1) avoidance of the endpoints

2) tendency towards the mean

3) minimum information gain

For example; on a 10 point scale, very few (> .5% of respondents) will mark a 1 or 10 (this is problem 1). In addition, 5's are over represented VS the expected amount of 4's and 6's (problem 2).

These problems together reduce the amount of information inferable from the collected data. There is a number of ways to measure this, including information theory (think of the avoidence of the end points and tendency towards the mean as a lossy compression algorithm for the true signal) or as a sampling of an unrepresentative population to infer the posterior distribution.

A 100 point scale has the same problems as above, and in addition suffers from a lack of consistency (reproducibility) - respondents are likely to give a product a different score (say a 92 and 94) when asked about the same product multiple times. This will frequently lead to non-parametric rank reversals, which 1) prove that a 100 point scale is not a "metric" and 2) show that the amount of information is further reduced at higher optionality.

Thus - the discrete scales that work best are:

A) 1 - 7

B) 1 - 13

as they both do not suffer from avoidance of the end points, both have no selectable mid-point (forcing respondents to choose a point above or below the median), and are highly replicable (very few respondents will switch rank orders).

I would help organize a NYC meetup; let's coordinate via email or the like?