Research Scientist, Sampling

Job description

DESCRIPTION

Are you interested in working with a group of high performing engineers to increase product adoption using ML? Are you interested in a team which has minimal operations? Are you interested in developing core business skills to become an effective all round leader? Are you interested in innovating while maintaining a healthy work life balance?

Sampling is a team which fits all the above criteria

The Team: Sampling is a program in Consumables which ensures the right customers are exposed to new products. Using ML we determine which new products will delight which set of customers ensuring a high conversion for our partner Brands. Sampling sends out free samples to customers which have higher likelihood of conversion than display ads. The Sampling program has an interesting mix of challenges around targeting, fulfillment and CX which will challenge you to develop innovative solutions and help you gain both technical and business skills.

The Role: As a Research Scientist on the Sampling team, you will be responsible for a key component of the product we offer - how we target our samples. To do this will require cross-domain efforts to gather and use the right data, and a spirit of discovery. You will also be responsible for devising models to evaluate the efficiency of campaigns, and learning models that cover different campaigns over time and assist vendors in setting up future campaigns.

The Org: The Consumables org comprises of various programs which work together to ensure maximum synergy. The org leadership has high focus on personal development and high throughput through efficiency and maintaining a healthy work-life balance (we have no meeting Mondays and WFH alternate Fridays J)

Desired profile

BASIC QUALIFICATIONS

· Masters or PhD in Computer Science, Engineering, Machine Learning, Operations Research or similar discipline
· 2+ years of relevant academic research or industry experience in developing algorithms
· Depth and breadth in state-of-the-art approaches in forecasting, planning or machine learning
· Ability to develop system prototypes in simulation
· Fluency in at least one statistical software package such as R, Matlab
· Scientific mindset and the ability to invent, a track record of thought leadership and contributions that have advanced the field
· Excellent creative problem solving skills
· Some experience with programming languages such as Java, C++, or Python