Сleverbridge is looking for a Data Science Engineer to build a new intelligence data platform based on current POC.



Our customer, as a proven leader in global commerce, provides flexible E-commerce solutions for monetizing digital goods, online services, and SaaS. Their cloud-based E-commerce platform simplifies recurring billing, optimizes the customer experience, and offers comprehensive global payment capabilities. Leveraging customers' expertise, technology, and services, clients effectively increase customer acquisition and retention while rapidly expanding into international markets for revenue growth.



Responsibilities:

• Work with large, complex data sets
• Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed
• Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations
• Build and prototype analysis pipelines iteratively to provide insights at scale
• Develop comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development
• Research and develop analysis, forecasting, and optimization methods

• 2+ years of experience in Data Science
• Extensive experience with Python and SQL
• Hands-on data engineering experience with pandas, Spark
• Highly skilled in Data Analysis
• Strong understanding of machine learning and statistics
• Experience productionizing ML models and managing ML models lifecycle
• Understanding of MLOps
• Experience with AWS SageMaker
• Experience working in high performing, agile environment
• Balance development with collaborative meetings
• English upper-intermediate or higher

• Flexible working format — remote, office-based or flexible
• A competitive salary and good compensation package
• Flexible and personalized career growth
• Professional development tools (mentorship program, tech talks and training, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Paid vacation days, sick leaves, and days off
• Healthcare & Sport program
• Medical insurance
• Memorable anniversary presents
• Corporate events and team buildings