> Markdown version of [/jobs/ext/2722319-data-scientist](https://www.wearedevelopers.com/jobs/ext/2722319-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Special Agents Mutual Benefit Association - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** A/B Testing, Code Review, Information Engineering, Python (Programming Language), Samba (Software), Feature Engineering, Delivery Pipeline, Model Validation, Pyspark, Information Technology, Production Code, Power Analysis (Cryptography), Data Analytics, Xgboost, Machine Learning Operations, Data Pipelines, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/data-scientist-samba-tv-7927583 ## About the Role * 5-7 years of professional data science experience - hands-on, delivery-focused, and measurable in shipped models and production systems * Expert-level Python - clean, modular, testable, production-ready code is your standard, not your aspiration * Advanced PySpark and Databricks - comfortable building and optimizing data pipelines and ML workflows on billion-row datasets * Deep, first-principles command of statistics and ML - you can explain from the ground up how these models work and you apply this understanding to make better modeling decisions * Solid grasp of experimental design - A/B testing, randomization, power analysis, and the conditions under which observational causal inference is appropriate * Fluent in the full ML lifecycle: feature engineering, model evaluation, deployment pipelines, drift monitoring, and iterative improvement in production * Hands-on experience with uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches applied to advertising or media outcomes * Strong ownership mindset - you drive projects independently and are comfortable owning your models from data exploration through production delivery, with minimal hand-holding. * Clear communicator - able to translate statistical reasoning and model behavior into language that drives decisions with product, engineering, and leadership * Experience with multi-touch attribution (MTA) or multi-channel attribution modeling - understanding of the limitations of rule-based approaches and the methodological trade-offs of data-driven alternatives * Hands-on experience with Causal ML methods - counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation - applied to advertising or media measurement outcomes * Direct exposure to TV or digital viewership data - ACR signals, STB data, viewership panels, or cross-platform measurement (linear + CTV/OTT) * Familiarity with the measurement * t vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC, GRP/TRP frameworks) * Advanced degree (MS or PhD) in Statistics, Mathematics, Computer Science, or a related quantitative field - or equivalent depth demonstrated through work ## Description We are looking for a hands-on Data Scientist to own and deliver complex measurement science and modeling work at the core of our measurement and audience sciences products. The role requires a deep, first-principles understanding of data science and machine learning - not just the ability to apply libraries, but the ability to reason clearly about model behavior, articulate trade-offs between approaches, and make defensible methodological decisions under ambiguity. This is emphatically a coding role - you will spend the majority of your time writing production-quality Python, building and evaluating models on large-scale viewership and web data, and delivering end-to-end ML solutions. You will work closely with Data Engineering, Product, and go-to-market teams., * Write and own production-quality Python code end-to-end - well-structured, tested, documented, and built to last; PySpark proficiency is essential for working with Samba's billion-row viewership datasets * Design, build, and deploy measurement models and statistical frameworks that power Samba's campaign measurement, reach/frequency estimation, and cross-platform attribution products * Apply the right statistical and ML technique to the right problem - drawing from hierarchical models, Bayesian inference, gradient boosting, regularized regression, causal ML, and probabilistic record linkage - and clearly articulate the reasoning behind your choices * Build and evaluate multi-touch and multi-channel attribution models; apply Causal ML methods - counterfactual modeling, meta-learners (S-learner, T-learner, X-learner), and heterogeneous treatment effect estimation - to advertising and viewership measurement problems * Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable, scalable, and production-ready * Lead technical design reviews and contribute meaningfully to architecture decisions across the Data Science team * Mentor junior Data Scientists through code review, pairing, and structured technical feedback - raising the team's technical floor * Communicate measurement methodologies and findings clearly to technical and non-technical audiences, including senior leadership and external clients, Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Anomaly Detection - Using unsupervised Machine Learning for detecting anomalies in customer base](https://www.wearedevelopers.com/videos/6-anomaly-detection-using-unsupervised-machine-learning-for-detecting-anomalies-in-customer-base) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)