Lead Data Scientist

Key Skills

Deep Learning, Image processing, Linux Operating system, Machine learning techniques, MongoDB, Natural Language Processing (NLP), NoSQL, Python Programming, R Programming, RDBMS, Statistical modeling, XGBoost

Job Description

Experience: 10 + years of overall experience, with minimum 6 years into core Data Science domain

• Ability for the following: Stakeholder management, Team leading and management, Client interaction
• Ability to understand a problem statement and implement analytical solutions & techniques independently with independently/proactively/thought-leadership.
• Work with stakeholders throughout the organization to identify opportunities for leveraging company/client data to drive business solutions.
• Fast learner: ability to learn and pick up a new language/tool/ platform quickly.
• Conceptualize, design, and deliver high-quality solutions and insightful analysis.
• 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.
• Collaborate and Coordinate with different functional teams(engineering and product development) to implement models and monitor outcomes.
• Ability to deliver AIML based solutions around a host of domains and problems, with some of them being: Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization

Experience Required:

• Expert level proficiency in at least one of R and Python.
• Ability to create efficient solutions to complex problems. Strong skills in data-structures and ML algorithms.
• Experience of working on end-to-end data science pipeline: problem scoping, data gathering, EDA, modelling, insights, visualizations, monitoring and maintenance.
• Problem-solving: Ability to break the problem into small parts and applying relevant techniques to drive required outcomes.
• Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms. You will be required to discuss and use various algorithms and approaches on a daily basis.
• We use regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modeling, dimensionality reduction, SEM, GLM, GLMM, clustering, Deep learning etc. on a regular basis. If you know few of them you are good to go.

Good to Have:

• Experience in one of the upcoming technologies like deep learning, NLP, image processing, recommender systems
• Experience of working in on one or more domains:
• CPG: pricing and promotion analytics, marketing analytics, trade promotions, supply chain management
• BFSI: cross-sell, up-sell, campaign analytics, treasury analytics, fraud detection
• Healthcare: medical adherence, medical risk profiling, EHR data, fraud-waste-abuse
• Experience in working with Linux computing environment and use of command line tools like sed/awk
• Good grasp on databases including RDBMS, NoSQL, MongoDB etc.
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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