— 1.5+ years of relevant work experience
— Strong level in at least one of Python/R.
— 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.
— Good knowledge of probability theory, statistics, and algorithms.
— Knowledge of at least few approaches like regression, tree-based learners, SVM, RF, XGBOOST, LightGBM, time series modeling, Bayesian methods, dimensionality reduction, clustering, Deep learning etc.
— Ability to break the problem into small parts and applying relevant techniques to drive required outcomes.
— Upper-Intermediate English.
— Experience in technologies like deep learning, NLP, image processing, recommender systems
— Experience of working in on one or more domains: CPG (marketing analytics, 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).
— Good grasp on databases including RDBMS, NoSQL, MongoDB etc.
— Best team: a multicultural team of bright specialists and friendly, helping people
— Challenge: plenty of complex and exciting projects from international clients
— No micromanagement: we encourage self-organization and trust
— Income: competitive salary and end-year bonuses
— Vacation: paid leave of 27 business days per year
— Learning and professional development: access to company learning platforms with free courses, external certifications and learning programs, free English classes
— Being healthy: free health insurance
— Communication: company parties, celebrations, workshops in different locations, cross-locations and cross-projects exchange programs
— Conceptualize, design and deliver 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, Marketing Mix Optimization.
— Conduct research, prototype models, gather data, scope and design architecture for solutions; consult clients and internal stakeholders on advanced statistical and ML problems.
— Collaborate and Coordinate with different functional teams (engineering and product development) to implement models and monitor outcomes.
The Artificial Intelligence and Machine Learning (AIML) group at Fractal Analytics is actively involved in helping Fortune 500 companies by enabling them to discover how they can leverage their data using advanced and sophisticated AI/ML algorithms for which we are looking for Data Scientists with the capability to work on independent statistical and machine learning research/ projects. If you are a problem solver with a curiosity for exploring new techniques and technologies in AIML space, then we would like to talk with you.