• Own experimentation (the heart of the role). Partner with Product and Commercial teams to design, run, and read growth experiments — from framing the hypothesis and sizing the test to calling the result and pushing the decision. Bring rigor (power analysis, causal inference, guardrail metrics) to a business moving fast. • Build the reporting backbone. Own the core dashboards and self-serve tooling the segment runs on, evolving an AI-augmented reporting stack that already automates much of the routine work. Your job is to make performance easy to understand for execs. • Generate insight, not just analysis. Break down revenue and margin performance into drivers - volume, mix, pricing, cohort behavior - and proactively tell us where growth is coming from, where it's leaking, and what to do next. • Keep the data foundation healthy. Manage the partnership with our central Data Engineering team to make sure the segment's core data models and pipelines support the analytics. • Sharpen the forecast. Support Strategic Finance with driver-based revenue forecasting analytics, connecting operational signals to financial outcomes.

• Collect, clean, and preprocess structured and unstructured data from multiple sources. • Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies. • Develop and test predictive models using statistical and machine learning techniques. • Assist in building data pipelines for data collection, transformation, and validation. • Create dashboards and visualisations using Power BI, Tableau, or Python libraries to communicate insights. • Write SQL queries to extract, manipulate, and analyse large datasets. • Support feature engineering and model optimisation to improve prediction accuracy. • Evaluate model performance using appropriate metrics and validation techniques. • Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. • Prepare reports and presentations summarising analytical findings and recommendations. • Document methodologies, code, and model assumptions to ensure reproducibility. • Assist in automating repetitive data processing and reporting tasks using Python or R. • Conduct research on emerging AI, machine learning, and data science techniques. • Ensure data quality, integrity, and compliance with organisational data governance standards. • Participate in team meetings, code reviews, and knowledge-sharing sessions.

• Own retailer onboarding from kickoff through go-live. • Manage weekly scan data submission health across the full retailer base. • Serve as the primary point of contact for all retailer and CPG partner communications. • Publish the weekly health dashboard for program performance. • Coordinate with Scan Data Engineering to ensure technical setup and test submissions are completed. • Monitor each submission cycle and communicate directly with retailers on action items.

• Serve as lead for programming, analytics, and statistics when working collaboratively with teams of health services researchers and business analysts to draw insight and intelligence from large administrative claims datasets, electronic medical records and various healthcare registry datasets. • Identify and develop solutions that can be implemented to key strategic business problems using high-level modeling and statistical analyses techniques. • Utilize SQL to perform advanced-level data extraction, transformation and data management; fully document and manage library of source code and algorithms for future use. • Identify, develop and test hypotheses in support of research and product offerings, and communicate findings in a clear, precise, and actionable manner to our clients. • Respond to and lead highly complex operational data requests and create ad-hoc queries to support research projects. • Provide quality control, quality assurance and review for projects where not the lead including solution orientated approaches and mentoring for cross functional training across the functional project teams. • Serve as lead when working closely with Inovalon’s Enterprise Data Management, Data Integration, MORE2 Registry®, and iPORT+™ teams to identify, understand, and resolve data issues and improve the efficiency, productivity and scalability of Avalere and Inovalon Product and production data processes. • Troubleshoot complex production-related issues and coordinate successful resolution. • Assist with the evaluation of data analytic vendors and tools. • Maintain compliance with Inovalon’s policies, procedures and mission statement. • Adhere to all confidentiality and HIPAA requirements as outlined within Inovalon’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the undertaking of the position. • Fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success of the Company. • Uphold responsibilities relative to the separation of duties for applicable processes and procedures within your job function. • We reserve the right to change this job description from time to time as business needs dictate and will provide notice of such.