Senior Data Scientist
We are looking for a Senior Data Scientist to join a modern, fast-paced tech environment and scale up our data science capabilities.
Your core mission will be to leverage advanced machine learning and statistical modeling to drive high-impact business decisions. You will focus on building robust models that measure the effectiveness of various business initiatives, optimize the allocation of large-scale budgets, and maximize overall operational efficiency. If you are passionate about transforming vast amounts of data into actionable, strategic insights, we want to hear from you.
Essential functions
End-to-End Ownership: Design, implement, and operationalize statistical and machine learning models from data collection to production.
Advanced Modeling: Leverage data to measure incrementality and performance across various channels, helping the business understand the true impact of its investments.
Drive Experimentation: Design, execute, and analyze experiments to validate hypotheses and complement your models with ground-truth data.
Cross-Functional Collaboration: Work closely with engineering, product, and business stakeholders to translate complex objectives into concrete, data-driven strategies.
Lead & Mentor: Act as a senior technical voice within the team, jumping into complex problem-solving as challenges arise and sharing knowledge with peers.
Qualifications
Educational Background: Bachelor’s, Master’s, or PhD in Statistics, Physics, Economics, Mathematics, Data Science, or a related quantitative field.
Experience: 3+ years of commercial experience as a Data Scientist.
Programming & Stack: Fluency in Python and its scientific stack (Numpy, Pandas, Scikit-learn, Matplotlib).
Core ML & Statistics: Deep practical knowledge of Linear regression, Gradient tree boosting, Gradient-based optimization, and classifiers.
Data Engineering Basics: Strong SQL skills to retrieve, manipulate, and analyze large, heterogeneous datasets.
Crucial Non-Technical Skills: Critical thinking, fast learning, and exceptional communication skills to translate technical outcomes to non-technical stakeholders.
Would be a plus
Domain Knowledge: Practical experience with Media Mix Models (MMM), attribution models, or budget-optimization techniques.
Advanced Modeling: Experience with Bayesian forecasting models and estimating statistical uncertainties.
Cloud & DevOps Tools: Experience working with Databricks, AWS, Git, and Docker.
Industry Experience: Previous exposure to large-scale consumer or e-commerce data.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.Apply to the position
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Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process.
All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.