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Designs and builds scalable data science and ML solutions for retail analytics, delivering data-driven insights to drive business decisions and innovation.
Senior Data Scientist builds predictive models and AI-driven analytics to improve decision-making, operational efficiency, and financial outcomes for a global immigration law firm using Python, SQL, and enterprise data platforms.
Directors AI and Data Science focused on marketing measurement and effectiveness, leading a team to design, execute, and interpret marketing mix modeling, attribution, and experimentation programs using AI/GenAI in production, managing client relationships and scaling measurement solutions.
Director of AI & Data Science for Marketing Measurement & Effectiveness at Artefact, leading measurement programs, statistical modeling, and data science teams for clients, with a focus on marketing mix modeling, attribution, and AI applications in production environments.
Leads AI/ML engineering teams to design and deploy production-grade AI solutions (LLMs, classical models, agent systems) for consulting clients, focusing on architecture, context engineering, and fine-tuning pipelines while supporting pre-sales and strategy.
Engages with customers and non-customers to provide differentiated service in bank branches; role focuses on client interaction and satisfaction.
Develops AI/ML models to optimize flight operations, maintenance planning, and crew scheduling using real-time data and predictive analytics for logistics efficiency.
Staff Data Scientist designs and implements growth and marketing analytics models to optimize lead scoring, marketing measurement, and spend allocation for a virtual behavioral healthcare company.
Staff Data Scientist at a behavioral healthcare startup, leading statistical modeling and causal inference to shape product and operational decisions using Python, SQL, and Snowflake.
A Staff Data Scientist at Charlie Health partners with Growth, Marketing, and Revenue teams to build measurement frameworks, scoring models, and causal inference methods that optimize spend and drive measurable outcomes in behavioral healthcare.
Staff Data Scientist at Charlie Health designs and implements statistical models and analyses to guide product, operations, and clinical decisions, using SQL, Python/R, and causal inference methods to improve mental healthcare access and outcomes.
About the role The Data Scientist applies statistical learning, predictive modeling, and analytic tradecraft to transform diverse data-economic, industrial, logistics, and geospatial-into mission insights. This role…
Develops AI/ML models and data tools to optimize aviation operations, including predicting flight delays, scheduling, and maintenance planning, ensuring scalable deployment and real-time decision support for crews and planners.
Leads a Data Science team to build and deploy AI-driven solutions for Sberbank’s salary-project client acquisition, overseeing full lifecycle from data research to production monitoring and business impact evaluation.
Develops and optimizes neural networks for Nintendo’s hardware/software tech, writing scripts for model training/evaluation and collaborating with teams on data procurement, model performance, and documentation.
Junior Data Scientist or Intern role based in Moscow. No specific daily tasks or core technologies are described in the posting.
Data Scientist intern focused on customer/user segmentation, based in Moscow. No further details provided in the posting.
A Data Scientist at Google Payments analyzes consumer payment data to drive business decisions, focusing on identity assurance and risk mitigation. Uses AI tools for workflows while designing measurement frameworks and influencing product roadmaps.
Builds and deploys predictive/prescriptive models for AbbVie’s healthcare business, bridging data science and business needs to drive data-driven decisions.
Builds and maintains credit risk/repayment models for Clair’s fintech platform, using ML to assess risk, predict user behavior, and optimize credit decisions. Works with transaction data, deploys models in production (AWS/Snowflake), and collaborates with product/risk teams.
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