Decision Point
2 weeks ago
Job Description : would a typical day at your work be like?
- 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.
What Do We Expect?
- 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. (ref:hirist.tech)
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