The Role
Own production Python and PySpark machine learning solutions for large-scale advertising and viewership data. Design measurement, attribution, and causal models; partner with Data Engineering on scalable pipelines; lead technical reviews; mentor data scientists; and communicate findings to technical, executive, and client audiences.
Summary Generated by Built In
Samba connects the advertising industry. Today, a trillion dollars of media flows through platforms that don’t talk to each other, and each one measures its own results. We built the independent alternative: consented first-party data and AI that give the world’s biggest advertisers, publishers, and platforms one clear view across all of it.
The next era of advertising will run on AI agents, and those agents will need data they can trust. We’re building that foundation, and the agents that act on it. Join us and help build what the industry runs on.
You own complex measurement science and modeling work at the core of Samba's measurement and audience sciences products. This is emphatically a coding role: most of your time goes to writing production Python and delivering end-to-end machine learning solutions on large-scale viewership and web data. You work closely with Data Engineering, Product, and go-to-market teams.
- Own Production Code: Write and own production-quality Python end to end, well-structured, tested, and documented, with PySpark proficiency essential for Samba's billion-row viewership datasets.
- Build Measurement Models: Design, build, and deploy measurement models and statistical frameworks powering Samba's campaign measurement, reach and frequency estimation, and cross-platform attribution products.
- Choose the Right Method: Apply the right statistical or machine learning technique to the problem, drawing from hierarchical models, Bayesian inference, gradient boosting, regularized regression, and causal ML.
- Model Attribution: Build and evaluate multi-touch and multi-channel attribution models, applying causal ML methods such as counterfactual modeling and meta-learners to advertising and viewership measurement.
- Partner on Pipelines: Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable, scalable, and production-ready.
- Lead and Mentor: Lead technical design reviews, contribute to architecture decisions across the Data Science team, and mentor junior Data Scientists through code review and pairing.
- Explain the Findings: Communicate measurement methodologies and findings clearly to technical and non-technical audiences, including senior leadership and external clients.
What You Bring
- 5+ years of hands-on, delivery-focused data science experience, measurable in shipped models and production systems.
- Expert-level Python and advanced PySpark and Databricks, comfortable building and optimizing pipelines and machine learning workflows on billion-row datasets.
- A deep, first-principles command of statistics and machine learning, and a solid grasp of experimental design, including A/B testing, randomization, and power analysis.
- Fluency across the full machine learning lifecycle, including feature engineering, model evaluation, deployment pipelines, and drift monitoring, with hands-on experience in uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches applied to advertising or media.
- A strong ownership mindset, driving projects independently from data exploration through production delivery, and a clear communicator able to translate statistical reasoning into language that drives decisions.
- Experience with multi-touch or multi-channel attribution modeling and causal ML applied to advertising or media measurement, ideally with direct exposure to TV or digital viewership data such as ACR signals or set-top box data.
- Familiarity with the measurement vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and standards like MRC and GRP or TRP; an advanced degree (MS or PhD) in a quantitative field, or equivalent depth, is a plus.
Compensation
$168,000 - $228,000 a year
Samba expects to offer a On-Target Earnings (OTE) of $168,000 - $228,000 per year for roles to be performed in California; actual base salary offered will depend on various factors, including but not limited to, location, experience, and performance. Base salary is just one component of Samba's total compensation package for employees. Other rewards may include bonuses, short-term incentives, and long-term incentives. In addition, Samba provides health insurance, wellness offerings, life and disability insurance, a retirement savings plan, paid holidays and paid time off (PTO), and other employee benefits.
Samba is an equal opportunity employer.
Your personal information
We collect personal information directly from you when you apply. Where the law permits, we may also receive it from third parties, such as through background, employment, or reference checks. For details, see Samba’s Applicant Privacy Policy. For EU residents, Samba Inc. is the data controller.
Use of AI in hiring
We may use AI tools to help review applications, analyze resumes, or assess responses. These tools support our recruiting team. People make every hiring decision. To learn more about how we process your data, please reach out.
Skills Required
- 5+ years of hands-on, delivery-focused data science experience with shipped models and production systems
- Expert-level Python experience
- Advanced PySpark and Databricks experience building and optimizing large-scale data and machine learning workflows
- Strong command of statistics and machine learning
- Knowledge of experimental design, including A/B testing, randomization, and power analysis
- Experience across the machine learning lifecycle, including feature engineering, model evaluation, deployment pipelines, and drift monitoring
- Hands-on experience with uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches in advertising or media
- Experience with multi-touch or multi-channel attribution modeling and causal machine learning applied to advertising or media measurement
- Ability to independently drive projects from data exploration through production delivery
- Clear communication of statistical reasoning to technical and non-technical audiences
- Direct exposure to TV or digital viewership data, including ACR signals or set-top box data
- Familiarity with measurement vendors such as Nielsen, Comscore, VideoAmp, or iSpot
- Familiarity with MRC and GRP or TRP standards
- Advanced degree in a quantitative field, such as an MS or PhD, or equivalent depth
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The Company
What We Do
Samba is a media-intelligence company that combines consented first-party viewership data from streaming, linear TV, the web, and video games with AI to map content, audiences, and outcomes. Its platform gives advertisers, publishers, and media platforms insight into audience behavior and supports campaign planning, targeting, measurement, and optimization across channels. Samba’s data and analytics help clients understand audiences and make marketing decisions.
