Staff/ Principal Data Scientist

About Tunnl

Tunnl is building a future where artificial intelligence enables organizations to connect meaningfully with the people who matter most. We help organizations conduct research at scale, define the right audiences, surface real-time insights, identify optimal communication channels, and measure changing attitudes over time.

Tunnl serves brands, agencies, and advocacy groups alike - organizations navigating complex communications, reputational, and regulatory landscapes. These teams need smarter, faster ways to make audience-informed decisions that stand up to scrutiny and resonate across stakeholder groups. Whether you're building a brand, shaping public opinion, managing risk, or launching a new initiative, Tunnl empowers you to move from insight to impact with clarity & confidence.

Role Overview

As a Staff/Principal Data Scientist at Tunnl, you will own the design and delivery of machine learning systems that power audience intelligence, targeting, and measurement across television and digital channels.

You'll work at the intersection of data science and AdTech — building production-grade machine learning systems that directly shape how advertisers reach and measure their audiences at scale. This is a high-impact, senior IC role where your work will influence product direction and business strategy.

What You’ll Do

• Design, build, and deploy machine learning solutions for audience targeting, lookalike generation, and individual propensity scoring

• Own the complete ML lifecycle - from exploratory analysis and experimentation all the way through production deployment and operational monitoring

• Develop and ship production ML systems spanning self-supervised representation learning, vector similarity search, and supervised classifiers

• Leverage distributed computing (Spark/Databricks) and cloud data platforms (AWS, Snowflake) to build and run production ML pipelines at scale

• Ensure model quality through rigorous evaluation practices: from embedding validation and retrieval quality to supervised model calibration and production monitoring

• Engineer features at scale from demographic, behavioral, and identity data — including handling missing values, encoding strategies, and pipeline-level data quality validation

• Contribute ML logic directly into shared production services, working alongside data engineering, software engineering, and product teams

Qualifications:

• 8+ years of experience in Data Science or Machine Learning, with a proven track record of delivering high-impact end-to-end ML solutions

• Master-level proficiency in Python and SQL

• Strong experience with big data and cloud infrastructure (Spark/Databricks, AWS S3, or equivalents)

• Expertise deploying and maintaining production ML pipelines including batch model training, large-scale scoring runs, async job orchestration, evaluation and monitoring

• Strong experience in audience intelligence or AdTech, with deep knowledge of audience modeling, lookalike/similarity systems, and ML-driven targeting at scale

• Hands-on experience with vector similarity and approximate nearest neighbor systems (FAISS or equivalent) — including index construction, search quality tradeoffs, and production embedding serving

• Experience with software engineering best practices: git, automated tests, CI/CD, and code deployment

• Exceptional communication skills with the ability to influence technical and non-technical stakeholders

Preferred Qualifications:

• M.S. or PhD in computer science, applied mathematics, statistics, data science, or a quantitative field with strong ML/modeling foundations

• Experience with GenAI tooling and LLM integration — particularly building structured recommendation or explanation layers grounded in ML model outputs

• Experience with self-supervised or representation learning approaches, particularly Transformer-based architectures for structured or semi-structured data

• Production experience with PyTorch for deep learning and embedding models, scikit-learn and XGBoost for supervised classification pipelines

Why You Should Apply:

• Join a team driven by curiosity, teamwork, integrity, and a shared passion for solving big challenges.

• A friendly, welcoming, and supportive culture with regular social and team events.

• Comprehensive benefits with excellent medical, vision, and dental coverage.

• Health Savings Account (HSA) and Flexible Spending Account (FSA) options.

• Employer-paid life insurance & short-term & long-term disability, with other voluntary additional coverage available (accident, critical illness, hospital indemnity).

• Flexible hybrid work policy.

• Flexible unlimited paid vacation plus 80 hours of paid sick leave.

• 10 paid company holidays per year plus the week between Christmas and New Year’s off.

• 401(k) plan with 100% match up to 3%, plus 50% match up to 5% (subject to IRS limits).

• Cell phone reimbursement stipend.

• Monthly parking or commuter stipend for VA-based employees.