Live opening · Posted 18 days ago
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Description supplied by the original job listing.
Responsibilities:
Collaborate with various stakeholders to identify complex business problems and break them down into problems that can be solved with a data-driven solution.
Solve a wide range of Machine Learning sub-problems impacting different parts of Blinkit's demand and supply systems.
Translate business processes into mathematical models.
Prioritise problems identified in Blinkit's supply chain to decrease cost and increase efficiency, or work on the Demand side to increase Revenue and conversion.
Publish work that you've done in peer-reviewed journals. Represent Blinkit at conferences.
Requirements:
B. Tech / Masters in Computer Science / Statistics / Mathematics / Economics or related quantitative field with 3 - 5 years of relevant experience in areas like Machine Learning, Natural Language Processing, Artificial Intelligence, Computational Complexity, etc.
Strong foundations in the mathematical aspects of learning, including Linear Algebra, Probability Theory, Statistical Modelling, Analysis of Variance, Convex Optimisation, Hypothesis Testing, Data Structures, Multivariate Calculus, etc.
Hands-on experience in supervised machine learning methods like Decision Trees, Random Forests, Support Vector Machines, Neural Networks, Time Series, etc.
Knowledge of unsupervised and feature engineering machine learning methods like Principal Component Analysis, Clustering, Word2Vec, One-Hot-Encoding, etc.
Work experience in at least one Data Science Language (Python / R / MATLAB / Octave).
Proficiency in Database System Concepts and working knowledge of at least one database (SQL / NoSQL).
Strong understanding of all the stages of taking a Model to production, like scouting for Features, Data wrangling and cleaning, Feature engineering, choosing the right algorithms, validation techniques, working with large data sets, rolling out versioned Models in production using A/B Tests, measuring KPIs in production, etc.
Experience with big data tools like Spark and Hadoop is a plus.
Domain knowledge in Supply Chain and concepts like Queuing Theory, Inventory Management, Warehouse Layout Design, Forecasting Techniques, Genetic Algorithms, Game Theory, and Simulated Annealing is a plus.
Experience
3-6 yrs
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