• Partner with cross-functional teams to define high-impact product questions, success metrics, and decision frameworks. • Analyze user behavior, creator activity, content ecosystems, retention, growth, monetization, and social dynamics to identify opportunities and risks. • Design and analyze experiments, including A/B tests and other causal measurement approaches, to evaluate product launches, campaigns, and strategic initiatives. • Define and improve core product metrics, dashboards, diagnostic views, and recurring reporting that help teams understand what is changing and why. • Build durable analytical assets such as reusable notebooks, data marts, metric definitions, self-serve dashboards, and analysis templates. • Use AI-assisted and agentic workflows to accelerate analysis, automate repetitive investigation, improve documentation, and build lightweight internal tools for common analytical questions. • Collaborate with Data Engineering and product teams to improve data quality, instrumentation, modeling, and source-of-truth definitions. • Communicate findings clearly to technical and non-technical audiences, including senior stakeholders, and influence product decisions through evidence and judgment.

• Research, design, and build ML models across a range of use cases • Work across the full deployment spectrum: managed cloud ML platforms and containerized solutions built in Python • Collaborate with engineers to integrate models into production environments and uphold MLOps best practices • Preprocess and analyze large datasets; think critically about data quality and what it means for model reliability • Contribute to technical discussions across the team, fostering a culture of shared learning and continuous improvement • Translate complex ML concepts clearly for both technical collaborators and non-technical client stakeholders

• Own client engagements end-to-end: scope the problem, build the solution, manage expectations, and deliver • Lead small project teams and serve as the technical and strategic point of contact for clients • Design, build, and deploy ML solutions across a range of domains and use cases in a landscape where no two projects are the same • Work across the full deployment spectrum including managed cloud ML platforms (SageMaker, Vertex AI, Azure ML) and containerized Python solutions running on raw infrastructure • Mentor junior and senior data scientists and help shape how we practice ML at OneSix • Evaluate emerging tools and techniques and bring the right ones to bear on client problems

Role Description This Data Scientist role will be a part of the Decision Sciences team in Client Center of Excellence organization. The role will be responsible for interpretation of data and business requirements to develop customer centric data driven insights and AI/ML solutions. Working in collaboration with Director, Decision Sciences and other data scientists team members, this role works to: - Assist in development of advanced AI/ML systems using techniques such as deep learning, representation learning, time-series modeling, survival analysis, and probabilistic modeling to solve complex healthcare problems. - Develop Generative AI and LLM-powered solutions including retrieval-augmented generation (RAG) pipelines, domain-adapted LLMs, and AI copilots for enterprise workflows. - Work with business stakeholders to develop business solutions based on data driven insights to solve complex business problems. - Be a key contributor in projects that combine diverse customer data sets to identify trends and opportunities, develop custom machine learning models, and provide recommendations to optimize the business and address data-related problems. - Coordinate with different functional teams to improve customer data architecture, ensure accuracy of model output and implement new data gathering processes. - Create customized summaries, business presentations and documentation for internal business clients based on the results of research. - Collaborate with engineering, platform, and product teams to operationalize scalable AI/ML and GenAI systems within enterprise platforms. Qualifications - High School Diploma/GED - 2+ years of experience providing data driven solutions, reports, analytics or recommendations using SQL and/or data visualization tools like PowerBI, Tableau or equivalent. - 1+ years of experience in leveraging machine learning, artificial intelligence, or applied data science to help answer business questions. - 1+ years of experience in Python-based machine learning development using frameworks such as PyTorch, TensorFlow, or equivalent. - 1+ years of experience designing and deploying production reporting, dashboards, ML models or supporting production ETL jobs. - 1+ years of experience of developing machine learning systems leveraging regression, natural language processing algorithms, classification and clustering, time-series forecasting and predictive/prescriptive modeling. Requirements - Experience working with distributed ML systems and large-scale data platforms such as Snowflake, Spark, Databricks, or other ML systems. - Experience working on cloud platforms such as AWS, Azure, or GCP. - Experience working with healthcare datasets and standards such as claims, EHR, ICD, CPT, SNOMED, FHIR, or HL7. - Experience working on development and support of data products in a business environment. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase. - 401k contribution (all benefits are subject to eligibility requirements).