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Data Scientist

Sambatv · San Francisco, California · On Site · Active · $150,000–$185,000 / year · Lever

Job facts

Field	Value
Company	Sambatv
Title	Data Scientist
Normalized title	-
Department / team	Engineering / Data Science & Analytics
Location	San Francisco, CA, United States
Work model	On Site
Employment type	US Full Time Salaried
Salary	$150,000–$185,000 / year
Status	active
ATS provider	Lever
Posted / first seen	2026-04-13 / 2026-05-29
Changed / last seen	2026-05-29 / 2026-06-06

Related slices

Page	What it contains	Open
Company jobs	Active postings from Sambatv.	Open
Company breakdowns	Role, location, ATS, and work model facets for this company.	Open
ATS provider jobs	Active postings observed through Lever.	Open
Provider filtered search	The same provider as a filtered job collection.	Open
City jobs	Active postings in San Francisco.	Open
Department jobs	Active postings in Engineering.	Open
Work model jobs	Active On Site postings.	Open
Lifecycle events	Open, update, close, and reopen events for this posting.	Open
Original posting	Canonical source or apply URL captured from the ATS.	Open

Linked records

Company	Sambatv
Source	d459f587-2ba3-486e-a163-d3a8ce07809e
ATS provider	Lever

Description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant. ABOUT THE ROLE 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. Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact. 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. WHAT YOU'LL DO 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 WHO ARE YOU 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

Full job record

Job ID	14d23900de914e183ed902c24577e2b894fa859d
Org ID	b04562e2-9dff-452b-aff5-a374f4791d19
Source ID	d459f587-2ba3-486e-a163-d3a8ce07809e
Board ID	d459f587-2ba3-486e-a163-d3a8ce07809e
Provider	lever
Provider Job Key	908e859d-5688-44f0-815f-8b74779b6f74
Title	Data Scientist
Normalized Title	—
Status	active
Active	yes
Location Text	San Francisco, California
Department	Engineering
Team	Data Science & Analytics
Employment Type	US Full-time Salaried
Workplace Type	on_site
Remote Policy	—
Country	United States
Region	CA
City	San Francisco
Salary Raw	USD 150000-185000 per-year-salary
Salary Min	150,000
Salary Max	185,000
Salary Currency	USD
Salary Period	year
Source URL	https://jobs.lever.co/sambatv/908e859d-5688-44f0-815f-8b74779b6f74
Apply URL	https://jobs.lever.co/sambatv/908e859d-5688-44f0-815f-8b74779b6f74/apply
First Seen At	2026-05-29 07:02:07Z
Last Seen At	2026-06-06 07:56:57Z
Last Checked At	2026-06-06 07:56:57Z
Last Changed At	2026-05-29 07:02:07Z
Inactive At	—
Source Posted At	2026-04-13 23:24:14Z
Source Updated At	—
Raw Payload Uri	s3://job-postings-prod-raw-590183727216/raw/provider=lever/board=sambatv/date=2026-06-06/2026-06-06T07-56-56-657Z-9b5c0775563cda1fb860ba88903689b62536e8683ebc3e8bd065ceb14662c401.json

Event Fields

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Extensions

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