Data Scientist (ML)

Published on Jun 24, 2021
Fractal Analytics

An Outsource company with office in Kyiv, Ukraine.

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1-3 years
Job Type:
Data Engineering
Data Science & AI

What You Will Do Responsibilities

— 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.

What You Should Bring

— 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.

What You Will Get Benefits

— 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

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