Details:

Job Responsibilities : 

- Provide thought leadership around advanced machine learning techniques 

- Conceptualize, design and deliver high-quality solutions and insightful analysis on a variety of projects ranging in both complexity and scope 

- Conduct research and prototyping innovations; data and requirements gathering; solution scoping and architecture; consulting clients and client facing teams on advanced statistical and machine learning problems 

- Provide solutions but not limited to Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization 

- Lead and groom the data scientist pool on solving complex problems using data science 

- Conduct ML training 

Qualification & Experience : 

- 6+ years of demonstrable experience designing ML/statistical solutions to complex business problems at scale. 

Mandatory : 

- Expert-level proficiency in at least one of R and Python 

- Expert-level proficiency and thorough understanding of at least one of the upcoming technologies like deep learning (DL), natural language processing (NLP), reinforcement learning (RL), and Bayesian methods. 

- Expert-level proficiency in statistical/ML predictive techniques such as regression/classification, clustering, dimensionality reduction, forecasting, optimization etc. 

- Working experience and statistical clarity in traditional algorithms like linear models, time series models, dimensionality reduction techniques, tree-based learners (Random Forests etc.), kernel based learners (Support Vector Machines etc.), Linear/Dynamic programming, Bagging/Boosting, ensembles etc. 

- Proficiency in articulating the algorithms to clients in a simplified manner 

Preferred : 

- Implementing machine learning at scale - building and implementing scaled solutions/ products 

- Demonstrable experience in formulating a problem statement and implementing analytical solutions by understanding available data and functional requirements 

Good to have knowledge on one or more domains : 

- CPG, BFSI, Healthcare, Logistics, Manufacturing etc. 

- Fair understanding of distributed computing in multicore and/or clusters, especially using R/Python. 

- Experience working within a Linux computing environment, and use of command line tools for automating common tasks. 

- Knowledge and familiarity with the big data stack - Hadoop, hive, spark, map reduce and other big data tools and technologies 

- Operating knowledge of cloud computing platforms (AWS, especially EMR, EC2, S3, and the AWS CLI) 

- Thorough grasp data structures including RDBMS, NoSQL, MongoDB etc. 

- An ideal candidate would have great problem-solving skills, the ability & confidence to hack their way out of tight corners. 

Education : 

- MS / M.Tech (preferred) or BS / B.Tech. in a field with significant quantitative training such as Statistics, ML, AI, Physics, Mathematics, Economics, Finance etc.

Min. Qualification:

ug

Skills Required:

bfsi, clustering, deep learning, forecasting, hadoop, logistic regression, machine learning, nlp, No SQL, python, r, regression, statistical modeling, time series