Sr. Data Scientist - Measurement & Modeling Development

About the Role:

As the Senior Data Scientist, you will play a key role in: 

• Developing advanced marketing measurement and modeling capabilities (e.g., MMM, Forecasting) that unlock our company vision to transform the measure of marketing success. You will be at the forefront of developing and delivering differentiated AI-assisted marketing data science and measurement solutions focused on maximizing profitable enterprise revenue and customer value for our clients. 

• Partnering with driven, solution-minded experts, business leaders, analysts, and scientists at Ovative in engaging with clients, and defining approaches and road maps for solutions to client problems. 

• Technical mentoring of junior data scientists across modeling approaches, experimental design, and code quality — building depth in the quantitative methods that power our measurement and modeling products. 

• Working with technology leaders, product owners, and engineers to convert novel solutions developed into scalable new services and product offerings at Ovative. 

• Partnering with a larger Measurement & Modeling Development DS team to inform product roadmap priorities and emerging industry DS methodologies. 

• Being a part of an inclusive culture that inspires and motivates the team and attracts new, diverse technical talent to the organization. 

Responsibilities of a Sr. Data Scientist - Measurement & Modeling Development:

• Lead technical data science contributor in a high-performance multi-disciplinary team comprising data science, data engineering, and full stack members, responsible for your team’s productivity, operational excellence, and business impact. 

• Drive technical advancement across measurement and modeling products — co-owning model architecture, methodology, and feature development across aspects of work from POC through production-ready deployment. 

• Partner closely with Engineering and Product Management to scale your team’s innovative measurement and modeling solutions into product and service offerings. 

• Contribute to product development cycles within an agile environment, including sprint planning, backlog refinement, and translating research outputs into scalable, maintainable product features. 

• Provide mentoring, training, and other opportunities for effective technical development of data scientists. 

• Assist with technical parts of business development as needed, including RFP response, sales, and conference presentations using AI assistance where applicable. 

• Build strong relationships across the organization to understand internal stakeholder needs for trusted data science support. 

Requirements:

• 3+ years of hands-on experience in data science or a related quantitative field, with a strong track record of delivering business value through technical innovation. 

• Experience contributing to product-centric data science teams, including working within agile development cycles and translating research outputs into scalable, maintainable product features. 

• Expertise in machine learning, advanced statistical modeling, and optimization algorithms, with hands-on experience in the areas listed below. 

• Demonstrated expertise in object-oriented programming in Python and statistical programming in R, with industry best practices in writing scalable and maintainable code. 

• Bayesian / Media Mix Modeling (MMM) experience.

• Experience with time-series modeling and/or forecasting methods. 

• Expertise with linear algebra and advanced statistical modeling. 

Preferred Technical Qualifications: 

• Hands-on experience with optimization solvers (e.g., Gurobi, Pyomo) and the underlying algorithm classes that power them, including gradient-based, convex, and greedy method.

• Experience with attribution modeling. 

• Applied experience integrating AI-assisted development practices into DS workflows, including code generation, methodology exploration, and documentation. 

• Familiarity with cloud infrastructure and deployment practices (e.g., AWS/GCP/Azure), MLOps pipelines, and containerization. 

• Strong business acumen, especially within digital and traditional marketing domains; ability to translate data insights into clear strategic recommendations. 

• Excellent communicator: able to lead conversations with technical and non-technical stakeholders, including senior client partners and internal executives. 

• Demonstrated leadership and mentorship skills; able to think independently, guide junior team members, and influence cross-functional teams. 

Preferred Programming and Data Environments: 

• Languages: Python and R 

• Tools: Git, Docker, Poetry, Azure 

• Data platforms: BigQuery, Databricks 

• Familiarity with cloud infrastructure and deployment practices (e.g., AWS/GCP/Azure), MLOps pipelines, and containerization.