• Understand business requirements and translate them into analytical solutions and machine learning models; • Work across the entire data lifecycle: exploration, preparation, modeling, validation, and deployment; • Develop and maintain data pipelines and models in production; • Apply exploratory data analysis techniques, feature engineering, and statistical modeling; • Build supervised, unsupervised, and time series models; • Perform model validation, comparison, and performance monitoring; • Ensure operationalization of solutions in production environments, focusing on scalability and performance; • Present results to stakeholders, translating technical analyses into business insights; • Ensure adherence to architecture guidelines, data governance, and information security; • Contribute to the team's technical growth by proposing improvements, tools, and best practices.

• Bidra till utveckling och driftsättning av banbrytande AI- och maskininlärningslösningar • Hantera heltäckande AI-projekt, från dataförberedelse och modellering till produktionsdriftsättning och övervakning

Welcome to Decision Foundry - Data Analytics Division! We are proud to introduce ourselves as a certified "Great Place to Work," where we prioritize creating an exceptional work environment. As a global company, we embrace a diverse culture, fostering inclusivity across all levels. Originating from a well-established 19-year web analytics company, we remain dedicated to our employee-centric approach. By valuing our team members, we aim to enhance engagement and drive collective success. We are a leading Data Analytics & Salesforce consulting firm delivering transformative digital solutions for businesses across industries. Our expert team partners with clients to unlock the full potential of the Salesforce ecosystem, with a specialized focus on data-driven marketing, automation, and AI-powered personalization.  We win as an organization through our core tenets. They include: ·       One Team. One Theme. ·       We sign it. We deliver it. ·       Be Accountable and Expect Accountability. ·       Raise Your Hand or Be Willing to Extend it Role summary We are seeking a Senior Data Scientist to join the Data Insights team for our client who will be a key individual contributor, applying statistical rigor and advanced analytical techniques to extract value from the product and business data. This role requires a strong understanding of product usage to provide actionable insights that drive business strategy and feature development. This is a senior, hands-on analytical role focused on end-to-end ownership, independent execution, deep-dive analysis, and translating complex data into clear business recommendations. You'll work closely with Product Managers, Executive Leaders, and Engineering teams to define key metrics, measure product health, and inform data-driven decisions. Success in this role requires a strong foundation in statistics, advanced SQL skills, and proven experience in product experimentation and reporting for a technical audience. Responsibilities Product Analytics & Experimentation - Understand detailed usage of products by analyzing user behavior data, translating complex questions into analytical plans, and building robust product metrics. - Run and measure product experiments (A/B tests) from design through interpretation, clearly articulating results and recommendations to stakeholders. - Develop and maintain key performance indicators (KPIs) and operational metrics for product features and overall business health. Strategic Insights & Reporting - Provide actionable insights for Product Managers on user engagement, feature adoption, and growth opportunities to directly inform the product roadmap. - Build deep-dive reports for Executive Leaders on critical business trends and the performance of strategic initiatives, presenting findings in a clear, compelling narrative. - Collaborate with engineering teams on data logging, instrumentation, and ensuring the accuracy of product data pipelines. - Influence product and business strategy by framing data-informed tradeoffs and recommendations for senior leaders. Technical Execution & Modeling - Apply statistical modeling and machine learning techniques to solve business problems (e.g., churn prediction, segmentation, propensity modeling). - Design and implement data visualizations and self-service dashboards to democratize data access across the organization. - Ensure data quality and integrity for all analytical outputs and reports. Collaboration & Communication - Partner with cross-functional teams (Product, Engineering, Marketing, Sales) to define data requirements and analytical objectives. - Coach and mentor junior analysts and data scientists on best practices for data visualization, statistical analysis, and clear communication of results.

Role Description We are seeking a Statistical Geneticist with expertise in whole genome sequencing (WGS), proteomics, and clinical outcomes analysis to advance our research in identifying novel therapeutic targets. This role will involve analyzing large-scale biobank and population-cohort datasets to uncover genetic and molecular factors associated with disease risk, progression, and treatment response. You will operate as part of the CMR Data Science and Computational Biology (DSCB) team and partner with early discovery scientists and clinicians, translational scientists, bioinformaticians, and geneticists. Key Responsibilities - Apply statistical and computational approaches to analyze WGS/WES, proteomics, metabolomics, and clinical data for biomarker discovery. - Conduct rigorous analyses of large-scale population cohorts and biobank datasets to identify genetic variants and causal genes associated with disease outcomes. - Develop and implement machine learning and bioinformatics pipelines to integrate multi-omics data. - Collaborate with interdisciplinary teams, including geneticists, epidemiologists, and clinicians, to interpret findings and guide therapeutic development. - Prepare scientific reports, presentations, and publications detailing research outcomes. - Contribute to the development of novel statistical methods for analyzing high-dimensional biological data. Qualifications - PhD in statistical genetics, bioinformatics, computational biology, biostatistics, or a related quantitative field. - Qualified applicants must be authorized to work in the United States on a full-time basis. Requirements - Expertise in whole genome and whole exome sequencing analysis, proteomics, metabolomics and other molecular data analysis, and clinical outcomes research. - Strong proficiency in statistical modeling, machine learning, and high-dimensional data analysis. - Experience working with large biobank and cohort datasets (e.g., UK Biobank, All of Us, FinnGen). - Proficiency in programming languages such as R, Python, and SQL for data analysis. - Familiarity with genetic association studies, GWAS, and polygenic risk scores. - Excellent communication and collaboration skills to work effectively in cross-functional teams. - Experience in pharmaceutical or biotech industry settings. - Knowledge of functional genomics and multi-omics data integration. - Strong publication record demonstrating contributions to statistical genetics and biomarker discovery and analysis. - Prior experience in cardiometabolic research. - Prior experience with polygenic risk score models. Benefits - Attractive, market-leading salary package. - Clear career advancement path with professional development opportunities.