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  • 2 - 5 Years
  • Posted : above 1 month

Job Description:

Responsibilities

- Core Personalisation algorithms - these are used for driving re-seller engagement, offers, growth/retention strategies & product suggestions, app feed prioritisation - From understanding how to gather the data for cold-start recommendations, to collaborative filtering models, to incorporation of feedback so that the re-sellers are able to drive more business from the platform

- Develop models that help understand and describe resellers demog, selling cycle, acquisition pattern, reduce return, increasing the networks engagement & profit margin

- Operations research- every day we make many small (and large) decisions, from what products to procure, which resellers to target, where to enable or disable deliveries, reduce the return rate and improving overall efficiency Each of these decisions has a cost and benefit, along with competing trade-offs to consider

- Insights, Forecasting, and predictive models- to make smart decisions, we need to have a crystal ball that tells us with a degree of certainty what will happen in the future by leveraging from tons of data harnessed till now

Skill Sets

- B Tech, MS in a quantitative discipline (eg math, computer science, stats, physics, engineering, operations research)

- At least 2-year experience in data science in a similar industry/ Startups

- Strong SQL skills, Good hold of NoSQL databases

- High level of proficiency in R, Python, Scala or similar modeling/scripting language

- Strong hands-on knowledge in statistics, optimization, and experience developing and deploying machine learning & data visualization

- Experience developing and deploying machine learning algorithms that drive consumer engagement, forecasting, ranking & sorting, demand & logistics

- Prior experience in an ecommerce and scale-up environment preferred

Profile Summary:

Employment Type : Full Time
Salary : Not Mentioned
Deadline : 15th Mar 2020

Key Skills:

Company Profile:

Not Mentioned

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