Senior Data Scientist

data sciencemachine learningidentity resolutionentity resolutiongraph algorithmsScalaSparkSQLPythonGoogle CloudBigQueryDataprocKafkaLLMsAI-assisted developmentprivacy-by-designperformance marketingattribution

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Senior

Years experience

5-10

Location

Remote

Full job description

MNTN is hiring a Senior Data Scientist to develop methodologies, models, and graph-based approaches for identity resolution in Performance TV marketing. Responsibilities include designing graph-based identity resolution systems, analyzing large datasets using Scala, Spark, SQL, and cloud tools, contributing production-grade code, defining validation strategies, collaborating with cross-functional teams, leveraging AI tools for research and prototyping, and applying privacy-by-design principles. Requirements include 5+ years in data science or applied research with large-scale datasets, expertise in identity graphs and entity resolution, strong skills in Scala, Spark, SQL, and/or Python, solid foundation in statistics and machine learning, experience productionizing data science solutions, mentoring experience, and familiarity with AI-assisted workflows. Preferred experience includes adtech, martech, cloud-native data and ML tooling, graph algorithms, and privacy-enhancing technologies. This is a full-time remote role.

What you'll 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 for 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

Requirements

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 focused on correctness, explainability, scalability, observability, and maintainability
Entrepreneurial, customer-first mindset connecting identity science quality to marketing performance and attribution accuracy