MarketCast
Senior Data Scientist - Product Team
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Role Impact
As our Senior Data Scientist - Product Team, you'll be a pivotal player in our Data Science as a Service team.
The Senior Data Scientist - Product Team plays a pivotal role in designing, developing, and iterating the core machine learning models and analytical frameworks that power MarketCast's commercial product offerings. Operating at the intersection of data science and product development, this individual contributor translates complex mathematical and statistical concepts into scalable, repeatable product features that drive business growth. Daily responsibilities include collaborating closely with product managers, software engineers, and research teams to build robust, production-grade pipelines and novel methodology layers. By transforming complex, multi-source datasets into highly reliable, actionable intelligence, this role amplifies the consumer's voice and delivers market-leading advertising and brand insights to global entertainment and media clients.
We're Looking For
Product-Focused Model Development
The individual designs, builds, and validates advanced statistical models and machine learning algorithms that serve as the core intelligence engine for MarketCast's commercial SaaS offerings. This is achieved by utilizing modern machine learning frameworks such as PyTorch, XGBoost, and LightGBM to process complex consumer datasets. This development ensures that the analytical layer within the products remains robust, highly scalable, and capable of generating precise insights. Working in an embedded product structure, success is measured by the seamless integration and high performance of these models across a diverse range of client use cases.
Research Methodology & Innovation
The role continuously refines and develops the underlying measurement methodologies and scientific frameworks that differentiate the company's products in the market. This is accomplished by proactively evaluating and introducing cutting-edge techniques, specifically advanced natural language processing (NLP) and Generative AI frameworks. Implementing these advanced approaches ensures that product offerings remain scientifically rigorous, state-of-the-art, and aligned with modern data science practices. The individual collaborates with research insights teams to validate that new methodological approaches directly improve product differentiation and performance.
Product Strategy & Collaboration
This position acts as the primary data science liaison within cross-functional teams to shape product roadmaps and strategic feature definitions. The candidate actively translates business and market requirements into concrete, actionable technical specifications. This advocacy ensures that commercial product decisions are evidence-based, technically feasible, and aligned with long-term platform capabilities. By partnering closely with Product Managers and Researchers, the individual successfully balances commercial goals with technical integrity.
Prototyping & Experimentation
The individual leads rapid prototyping initiatives to test, iterate, and validate new modeling approaches and product concepts before full-scale engineering. This process involves designing and executing rigorous A/B tests, pilot programs, and benchmarking studies. Conducting these experiments mitigates development risk and ensures only high-performing, mathematically sound methodologies progress to the production pipeline. The candidate partners with engineering and product stakeholders to leverage experimental outcomes, successfully guiding the iterative product development lifecycle.
Infrastructure Integration & MLOps
This role contributes to the architectural design of scalable data processing workflows and feature engineering pipelines. The candidate collaborates with engineering teams to deploy models using cloud infrastructure, containerization tools, and modern MLOps pipelines. This technical integration ensures that machine learning workflows are highly performant, reliable, and capable of automated monitoring at scale. Success is defined by the creation of stable, production-grade systems that minimize latency and maintain high model accuracy in real-world deployment.
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Quality, Validation & Standards
The individual establishes and enforces rigorous standards for model validation, quality assurance, and testing across the entire product development cycle. This is executed by writing clean, testable code and maintaining comprehensive technical documentation for all methodologies. Implementing these strict validation protocols guarantees reproducibility, protects model integrity, and provides a clear foundation for future technical audits. The scientist coordinates with quality assurance and engineering teams to ensure that all deployed data science components consistently meet high accuracy thresholds.
Internal Enablement & Subject Matter Expertise
The position serves as an internal subject matter expert, explaining the mechanics and commercial value of embedded data science capabilities. This is performed by developing white papers, conducting technical training sessions, and supporting sales enablement activities. Demystifying complex algorithms helps commercial, client service, and research teams confidently articulate product value to global clients. Through close alignment with marketing and client services, the scientist ensures that technical innovations are translated into clear, value-driven business narratives.
Mentorship & Technical Leadership
The role provides active technical guidance, code reviews, and professional mentorship to junior data scientists within the team. This is delivered by hosting regular knowledge-sharing sessions, establishing coding standards, and sharing best practices in statistical modeling. Cultivating this collaborative environment fosters technical excellence, drives continuous improvement, and accelerates the professional growth of the team. By championing rigorous engineering and scientific standards, the individual successfully elevates the collective capability of the data science function.
Qualifications
You'll typically have 7 or more years' experience in data science, including several years building models and analytical frameworks that have shipped inside commercial products. We'd expect a master's or PhD in Data Science, Statistics, Computer Science, Economics, Mathematics, or another highly quantitative field, but we care far more about what you can do than what your degree certificate says. If you came to data science by a different route and have the depth described below, we want to hear from you.
You'll have deep expertise in statistical modelling and machine learning, with Bayesian statistics as a particular strength: hierarchical models, MCMC and approximate inference, prior elicitation, model checking and comparison, and substantial hands-on experience in PyMC, Stan, NumPyro or similar. You'll be equally comfortable with modern machine learning frameworks such as PyTorch, XGBoost and LightGBM, and you'll have applied or evaluated advanced NLP and Generative AI techniques in a product context. You'll have led prototyping and experimentation, including A/B tests and benchmarking studies, and you'll know how to take a method from proof of concept to production.
On the engineering side, you'll be proficient in Python and SQL, with strong pandas skills. Experience with Polars is a strong plus. You'll have worked with cloud infrastructure (ideally AWS), containerisation and MLOps tooling, and you'll write clean, testable, well-documented code. You'll have a track record of setting validation and quality standards that others follow.
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You'll have shaped product roadmaps alongside product managers and engineers, translated business requirements into technical specifications, and acted as the data science voice in cross-functional decisions. You'll have mentored junior data scientists, run code reviews and knowledge-sharing sessions, and be comfortable explaining complex methods to commercial and client-facing audiences through training, white papers or sales support.
Experience with TV viewing or advertising data, or the media and entertainment industry, isn't a prerequisite, but a genuine interest is. Above all, you'll be curious about what makes audiences tick and motivated to turn that curiosity into products clients rely on.
Who We Are
MarketCast measures what moves people. Powered by AI, trained on decades of verified consumer response data, along with proprietary technology, MarketCast is the marketing effectiveness partner for the world's most ambitious brands, connecting emotional resonance to real-world business outcomes across advertising, sponsorships, content, brand health, and advanced analytics. With category-deep expertise spanning sports, entertainment, travel, automotive, and consumer brands, our team of seasoned industry strategists brings unmatched human intelligence to every engagement, turning complex data into decisive action so brands know exactly what's working, why it's working, and what to do next.
At MarketCast, we don't just accept difference - we embrace it, support it, and thrive on it for the benefit of our global culture and success. MarketCast is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know.
Check us out on LinkedIn and at: www.marketcast.com
Our Values
Move The Needle
We turn insight into action and action into impact, acting with urgency and intention at every level, anticipating what's needed, executing with discipline, and driving outcomes that are measured and meaningful.
Client Success is Our Scoreboard
We win when our clients win. Delivering scaled, tech-enabled solutions that drive measurable impact and value to build lasting partnerships.
Grow Every Day
Expertise is earned continuously by investing in our craft, our colleagues, and our company.
Own It
Take responsibility for outcomes, not just outputs.
Benefits
- Free movie tickets!
- 29 days annual leave PLUS Bank Holidays
- Flextime with core hours between 10am and 3pm
- 2 days’ work from home, per week
- 4% match pension scheme
- Enhanced maternity pay
- Regular social events in both UK locations
- Professional growth and career development including LinkedIn Learning
In addition to your salary, MarketCast believes in providing a competitive total rewards package for its employees. All benefits are subject to eligibility requirements, and the terms of our official plan may be modified or amended from time to time.
GENERAL DATA PROTECTION REGULATION (UK GDPR) NOTICE: The organisation collects and processes personal data relating to its applicants, employees and former employees to manage pre-employment and employment relationships and post-employment obligations. The organisation is committed to being transparent about how it collects and uses that data and to meeting its data protection obligations. For further information on the information we collect, how it’s used, and how it's protected,
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