Fractal Analytics - Lead Data Scientist

Job Position :

- Our artificial intelligence and machine learning team needs hands-on Data Scientist with the capability to perform independent statistical and Machine Learning research. To develop & code production-grade novel algorithms for our business experimentation platform. If you are an exceptional data scientist with a zest for exploring new techniques and technologies and are passionate about the science of experimentation, then we would like to talk with you. Individuals should also be able to break down compels business problems into smaller components and implement ML approaches to empower the end business decisions.

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 for Fractal via Fractal Analytics Academy

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.