Senior Data Scientist

Company Overview:

Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work Institute and recognized as a Cool Vendor and a Vendor to Watch by Gartner.

Job Location:

• The team member will be a part of the Artificial Intelligence and Machine Learning, Algorithmic Decision-Making Team (AIML - ADM) and will be working in a fast-paced environment.
• They will be enabling clients to discover how they can leverage their data using advanced and sophisticated AI/ML algorithms.
• Data Scientists in the AIML-ADM team should have the capability to work on independent statistical and machine learning research/ projects.

Responsibilities:

• Ability to understand a problem statement and implement analytical solutions & techniques independently with independently/proactively/thought-leadership.
• Team management and strong stakeholder management skills
• Leadership skills to manage a span of Data Scientists
• 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 clients 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 Modelling, Churn Modelling, Lifetime Value Estimation, Forecasting, Recommender Systems, Modelling Response to Incentives, Marketing Mix Optimization, Price Optimization

Qualifications:

Required Qualifications:

• 5.6-11 years in core Data Science & Machine Learning projects
• 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 daily.
• We use regression, Bayesian methods, tree-based learners, SVM, RF, XGBOOST, time series modelling, dimensionality reduction, SEM, GLM, GLMM, clustering, Deep learning etc. on a regular basis. If you know few of them, you are good to go.

Preferred Qualifications:

• 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.

Education

B.E/B.Tech/M.Tech in Computer Science or related technical degree OR Equivalent