Decision Point - AVP - Data Science

A few examples of past and current projects at Decision Point.

- Predictive ordering - Prevent SKUs from going Out of Stock with ML based predictions.

- Price Simulator - Optimize product range prices so that the client maximizes profits.

- Promotion Analytics - From a myriad of promotions, figure out the performance of every promotion. Also create a promotions simulator where users can see in advance what kind of results to expect.

- Hyper-personalization solution - Personalize the experience for customers with tailor made call scripts, customized schemes etc.

- Asset Performance Assessment - Given client's budget to install coolers for some of the outlets, figure out the selection of outlets which will result in maximum ROI.

- Customer Segmentation - Segmenting the retailers/POS so that a manufacturer can design proper incentives.

- Sales/Demand Forecasting - Help clients plan their production/inventory by forecasting future demand.

JOB DESCRIPTION

Role and Responsibility

AVP owns the ML part of the solutions delivered to clients. The role requires the individual to bring together data science knowledge and business understanding to solve real world business problems and work in a collaborative team environment. Proficiency in verbal and written communication skills in English is important. Candidate should be research oriented and passionate to learn new technologies and adapt.

An ideal candidate will be/have:

- Designed, developed and delivered multiple machine learning projects including implementation in production

- Worked on a variety of Data Science projects

- Experience converting a business problem into a Data Science problem

- Strong grasp of ML and Time Series fundamentals and their applications in business

- Proficiency in Python (including pandas/scikit-learn)

- Experience in leading or guiding a team of data scientists/ML engineers

- Familiarity with relational databases and intermediate level knowledge of SQL

- A team player who can deliver under pressure

- An eye for detail, quick learner and can think out of the box

- Familiarity with cloud platforms

- Experience working with large data sets and tools like MapReduce, Hadoop, Hive, etc. and large data streaming technologies like Spark, etc. is a plus