Position: Data Scientist
Company: Grid Dynamics
Experience required: 3y
English level: upper

As part of the Enterprise Data team, the Data Scientist supports the development of next-generation data platforms by employing data analytics and various data science capabilities (i.e. machine learning). Incumbents will be part of an innovative and energetic team that develops capabilities which will influence our business model and help our customer build the next generation data platform. The Data Scientist will have access to the vast amount of data stored in heterogeneous formats. This person is supposed to handle complex problems independently and demonstrate analytical thinking. Data Scientist should be able to make judgments and recommendations based on the analysis and interpretation of data.

Requirements:

Strong hands-on experience in leading data science projects in one of the following areas: digital marketing, price management, inventory management, risk management
Deep understanding of the business domain, ability to break down business problems into data science problems
Deep expertise in at least one of the following areas: targeting models, attribution/spent/bidding models, time series forecasting, demand forecasting, risk analysis
Excellent understanding of statistics, basic ML methods, ensembles, deep learning and reinforcement learning methods. 
Strong hands-on experience with feature engineering, statistical modeling, model validation and production deployment using python, h2o, TensorFlow or similar. Good understanding of machine learning tools and libraries available on the market. 
Strong communication skills, ability and willingness to participate in pre-sale client calls and meetings. Ability and willingness to participate in both R&D and client-facing projects, lead a team of data scientist.
Proven conference speaking, blogging, or kaggle experience is a strong plus.
Educational/Previous Experience Requirements:

Minimum of a Bachelor’s degree in Statistics, Mathematics, Computer Science, MIS or related degree and seven (7) years of relevant experience or combination of education, training, and experience.
Master’s degree or Ph.D. in Statistic, Mathematics, or Computer Science and ten (10) years of experience highly preferred.
An equivalent combination of education, experience, and training.
Competencies and Behaviors: 

Analysis: identify and understand issues, problems, and opportunities; compare data from different sources to draw conclusions.
Communication: clearly convey information and ideas through a variety of media to individuals or groups in a manner that engages the audience and helps them understand and retain the message
Exercising judgment and decision making: use effective approaches for choosing a course of action or developing appropriate solutions; recommend or take action that is consistent with available facts, constraints and probable consequences
Technical and professional knowledge: demonstrate a satisfactory level of technical and professional skill or knowledge in position-related areas; remains current with developments and trends in areas of expertise.
Building effective relationships: develop and use collaborative relationships to facilitate the accomplishment of work goals
Client Focus: make internal and external clients and their needs a primary focus of actions; develop and sustain productive client relationships.
We offer:

Opportunity to work on bleeding-edge projects
Work with a highly motivated and dedicated team
Competitive salary
Flexible schedule
Medical insurance
Benefits program
Corporate social events
Professional development opportunities

About us:

Grid Dynamics is the engineering services company known for transformative, mission-critical cloud solutions for retail, finance and technology sectors. We architected some of the busiest e-commerce services on the Internet and have never had an outage during the peak season. Founded in 2006 and headquartered in San Ramon, California with offices throughout the US and Eastern Europe, we focus on big data analytics, scalable omnichannel services, DevOps, and cloud enablement.