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.
As part of the Enterprise Data team, the Data Scientist will support the development of next-generation data platforms by employing data analytics and various data science capabilities (i.e. machine learning) and 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. The Data Scientist should be able to make judgments and recommendations based on the analysis and interpretation of data.
- Analyse and understand the business model, profile/analyse the data stored in various heterogeneous formats, and help develop data insights
- Identify patterns in the data and prepare an inventory of items which could be developed/trained using data science capabilities like machine learning
- Utilise appropriate pre-built models or help develop new models to predict and derive insights from heterogeneous data stores
- Ability to explore and implement advanced technology solutions such as machine learning
- Ability to identify unique data sets and information that may be useful for model development and analysis
- Under limited direction, seeks to understand what moves the needle for our financial advisors and our overall business model and explores data that could be helpful
- Performs other duties and responsibilities as assigned
- Strong theoretical and practical experience working with deep learning algorithms for images
- Experience with various Machine Learning techniques
- Good practical experience with Python
- Working knowledge of Big Data Technologies (Cassandra, Redis, Spark are the most important)
- Good communication and presentation skills and the ability to explain technical concepts to a non-technical audience
Educational/Previous Experience Requirements:
- Minimum of a Bachelor’s degree in Statistics, Mathematics, Computer Science, MIS or related degree and five (5) years of relevant experience or combination of education, training, and experience
- Master’s degree or Ph.D. in Statistic, Mathematics, or Computer Science and seven (7) years of experience highly preferred
- An equivalent combination of education, experience, and training
Competencies and Behaviours:
- 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; remain 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.
- 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
- 24 days annual leave + an additional of 5 sick days
- Floating Holidays
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