Senior Data Scientist
WFA Digital Insight
As demand for data-driven marketing solutions grows, the need for skilled data scientists with expertise in AI and graph-based entity resolution is on the rise. With a 25% increase in companies investing in Connected TV advertising, professionals with experience in large-scale data science and machine learning are in high demand. MNTN, a pioneer in this space, offers a unique opportunity to shape the future of Performance TV marketing. With a commitment to innovation and a people-first approach, MNTN stands out in the industry. Before applying, candidates should be prepared to showcase their expertise in Scala, Spark, and SQL, as well as their ability to work in a fast-paced, remote environment.
Job Description
About the Role
At MNTN, a leader in Connected TV advertising, we're seeking a Senior Data Scientist to shape our sovereign identity data backbone. This role is crucial in powering targeting, bidding, measurement, and cross-device attribution for Performance TV marketing. As a Senior Data Scientist, you will be responsible for developing methodologies, models, and graph-based approaches that unify identity signals across fragmented data sources. Your expertise will help improve the accuracy, scalability, and interpretability of identity resolution.The role is part of a dynamic team that values trust, ambition, quality, radical honesty, and compassionate leadership. Our company culture is defined by our team members and their shared values, making MNTN a great place to work. We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising, and our self-serve technology makes running TV ads as easy as search and social.
As a Senior Data Scientist, you will have the opportunity to work on large-scale data science projects, leveraging AI-assisted development and graph-based entity resolution to drive innovation. You will be part of a team that is committed to innovation that empowers, not replaces, and values a people-first approach.
What You Will Do
- Design and improve graph-based approaches for identity resolution across devices, households, and identifiers to improve match quality, coverage, and stability.
- Use Scala, Spark, SQL, and cloud-native tools to analyze large identity datasets, build models, and productionize data science workflows.
- Contribute production-grade code to shared repositories, using strong engineering practices to build clear, scalable, and maintainable systems.
- Define validation strategies and measure model performance and business impact on targeting, measurement, and attribution.
- Help shape the team's approach to identity science and partner across Engineering, Product, and Analytics to deliver production-ready solutions.
- Leverage LLMs, AI editors, and agentic workflows to accelerate research, prototyping, documentation, testing, and iteration.
- Apply privacy-by-design principles to ensure identity science work is auditable, compliant, and aligned with governance standards.
- Collaborate with cross-functional teams to identify opportunities for growth and improvement.
- Develop and maintain technical documentation for data science workflows and models.
- Stay up-to-date with industry trends and advancements in data science and machine learning.
What We Are Looking For
- 5+ years of experience in data science, machine learning, or applied research working with large-scale datasets in production.
- Strong experience building identity graphs, entity resolution systems, record linkage pipelines, or related graph-based matching systems.
- Deep expertise in Scala, Spark, SQL, and/or Python for distributed processing, model development, and experimentation.
- Strong foundation in applied statistics, machine learning, graph algorithms, clustering, probabilistic matching, and model evaluation.
- Experience productionizing data science solutions in partnership with engineering, including testing, monitoring, and reproducibility.
- Experience mentoring data scientists and helping define technical direction across a team.
- Comfortable with AI-assisted workflows and modern development tools, including LLMs.
- Deep ownership mindset, caring about correctness, explainability, scalability, observability, and maintainability.
- Entrepreneurial, customer-first mindset, connecting identity science quality to marketing performance and attribution accuracy.
Nice to Have
- Experience with LLMs, AI editors, and agentic workflows.
- Knowledge of cloud-native tools and technologies.
- Familiarity with privacy-by-design principles and governance standards.
- Experience working in a fast-paced, remote environment.
Benefits and Perks
- Competitive compensation package.
- Opportunity to work with a leader in Connected TV advertising.
- Collaborative, dynamic work environment.
- Professional development opportunities.
- Flexible, remote work arrangements.
- Access to cutting-edge technologies and tools.
- Comprehensive benefits package, including health insurance and retirement plan.
- Generous PTO policy and paid holidays.
How to Stand Out
- Ensure your resume and cover letter showcase your expertise in Scala, Spark, and SQL, as well as your experience with large-scale data science projects.
- Be prepared to discuss your approach to graph-based entity resolution and how you have applied it in previous roles.
- Highlight your ability to work in a fast-paced, remote environment and collaborate with cross-functional teams.
- Showcase your understanding of privacy-by-design principles and governance standards.
- Research MNTN's innovative approach to Connected TV advertising and be prepared to discuss how your skills and experience align with the company's mission and values.
- Prepare examples of your experience with AI-assisted workflows and modern development tools, including LLMs.
- Be ready to discuss your experience with productionizing data science solutions and your approach to testing, monitoring, and reproducibility.
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