Role: DATA ANALYST
Location: work from home/BANGALORE
JOB DESCRIPTION:
- Manage end-to-end engineering solutions for Machine Learning at scale.
- Integrate data science solutions into tangible products.
- Write efficient and quality code that can work @ Wal-Mart scale
- Productionize ML models – tackle all model management challenges.
- Parallelize algorithms/model training to make use of distributed infrastructure and reduce training time significantly.
- Adopt Wal-Mart’s quality standards and develop and recommend process standards and best practices across the retail industry.
- Research, learn & adapt new technologies to solve problems & improve existing solutions
- Participate in events to build innovative solutions
- Design, build, test and deploy cutting edge solutions at scale, impacting millions of customers worldwide drive value from data at Walmart Scale
- Interact with data science groups across Walmart to understand their major engineering challenges, build and propose solution for them.
- Identify right open source tools to deliver product features by performing research, POC/Pilot and/or interacting with various open source forums
- Deploy and monitor products on Cloud platforms.
- Promote and support company policies, procedures, mission, values, and standards of ethics and integrity
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Education Required:
- Bachelor’s with 0-2 years of relevant experience
skills
- Experience in Analyzing the Complex Problems and translate it into data science algorithms
- Sound knowledge in several areas in core ML such as Forecasting, Classification, Data/Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Neural Networks, Deep Learning Algorithms.
- Experience in statistical learning: Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series, Dynamic/Causal Model, Statistical Learning, Guided Decisions, Topic Modeling
- Experience with big data analytics – identifying trends, patterns, and outliers in large volumes of data
- Strong Experience with one or more of Python and R
- Strong Experience with big data platforms – Hadoop (Hive, Pig, Map Reduce, HQL, Scala)
- Experience with Teradata, SQL and relational databases, data warehouse
Additional Preferred Qualifications:
- Domain Knowledge of one or more divisions in Retail
- Published papers or given talks in leading academic and research journals
- Published papers or given talks in Data Science Forums
- Hold data science related patents
- Experience with data warehouse platforms – No SQL Databases (Cassandra)
- Experience with GPU/CUDA for computational efficiency
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