Netflix

Analytics Engineer 5 - Identity & Signal

Netflix$330K — $500K+*
US-AnywhereRemote in United States
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Advanced degree (PhD or Master's) in Statistics, Mathematics, Computer Science, or a related field.
  • 5+ years of experience in building machine learning models on large-scale data.
  • Expertise in supervised learning with a focus on interpretable models.
  • Strong feature engineering skills and familiarity with ML lifecycle practices.
  • Proven ability to prototype and validate algorithms using production data.
  • Strong programming skills in Python and SQL.
  • Knowledge of ad-serving and campaign mechanics, including supply and demand-side considerations.

Responsibilities

  • Build and iterate supervised machine learning models predicting campaign delivery outcomes.
  • Model campaign outcomes considering inventory and advertiser objectives.
  • Design evaluation frameworks to assess model performance and robustness.
  • Own feature engineering and manage the team's feature store.
  • Ensure model outputs are interpretable for stakeholders involved in decision-making.
  • Collaborate with ML engineers to deploy models and monitor their performance.
  • Engage with cross-functional teams to define and adopt ML forecasting objectives.

Benefits

  • Health Plans
  • Mental Health support
  • 401(k) Retirement Plan with employer match
  • Stock Option Program
  • Disability Programs
  • Health Savings and Flexible Spending Accounts
  • Family-forming benefits
  • Life and Serious Injury Benefits
  • Paid leave of absence programs
  • 35 days of annual paid time off for full-time hourly employees
  • Flexible time off for full-time salaried employees.
Full Job Description

In 2022 we launched a new lower-priced, ad-supported tier, and we are building an in-house, world-class ad-tech ecosystem to give our members more choice and to offer advertisers a premium, better-than-linear-TV experience. We are looking for the founding members of this new business area for Netflix.

The Identity & Signals team builds the identity foundation of the Netflix ads business — the graph and matching systems that let us recognize the same person or household across signals, devices, and partner data sources, and that determine which signals we can responsibly and accurately use for targeting, measurement, and reporting. We build and maintain the identity graph, run and evaluate entity-matching and resolution pipelines, and manage relationships with identity providers so that advertisers and internal teams can trust the signals underneath every campaign.

This is a foundational role on a small, high-leverage team. You will build the analytics and data infrastructure that powers identity matching and graph construction — designing the tables, pipelines, and metrics that let the team and its stakeholders understand match quality, coverage, and drift over time. You'll work end-to-end: from raw signal ingestion, through matching logic and graph construction, to the dashboards and data products that make identity health visible and actionable across the company.

In this role, you will:

- Design, build, and maintain the data models and pipelines that support identity graph construction, entity matching, and identity resolution across first-party and third-party signals.

- Partner with data engineering and software engineering to productionize matching logic, ensuring pipelines are scalable, well-tested, and monitored for data quality and drift.

- Build metrics, dashboards, and analytics that quantify match rate, match quality, coverage, and graph stability, and that surface anomalies before they affect downstream campaigns.

- Work closely with data science to evaluate and improve matching algorithms, providing the clean, well-documented data and features needed to test and iterate on models.

- Manage and evaluate the analytics relationship with external identity providers (e.g., Experian, TransUnion, LiveRamp), including onboarding new sources, validating match performance, and monitoring ongoing data quality.

- Translate identity graph and matching concepts — nodes, edges, match confidence, deterministic vs. probabilistic matching — into clear, actionable insights for product, sales, and other non-technical stakeholders.

- Collaborate with product and cross-functional partners to define identity requirements, evaluate trade-offs (accuracy vs. coverage vs. privacy), and prioritize roadmap work.

- Communicate technical decisions, trade-offs, and results clearly to both technical and non-technical audiences at all levels of the company.

We are looking for:

- 5+ years of experience as an analytics engineer, data engineer, or similar role working with large-scale data.

- Experience working with graph data structures and graph-based data models (e.g., property graphs, graph databases, or graph analytics on top of relational/columnar stores).

- Familiarity with entity matching / identity resolution concepts — deterministic and probabilistic matching, fuzzy matching, blocking/candidate generation, and match quality evaluation.

- Knowledge of, or direct experience working with, identity providers such as Experian, TransUnion, LiveRamp, or similar data/identity partners.

- Strong SQL and Python skills, with experience building and maintaining production data pipelines.

- Experience designing data models, metrics, and dashboards that make complex technical systems understandable to non-technical stakeholders.

- Demonstrated ability to collaborate closely across data engineering, software engineering, data science, and product teams.

- Ability to work independently, drive your own projects, and make compelling cases for prioritization.

- Embodies the Netflix values while bringing a new perspective to continue improving our culture.

Nice to have:

- Experience with ad-tech identity concepts — cross-device identity, household graphs, cookie/ID deprecation, or media measurement.

- Experience with graph databases or graph-processing frameworks (e.g., Neo4j, Neptune, GraphFrames, or similar).

- Familiarity with our ML/data stack (Metaflow) or comparable large-scale data tooling.

- Experience working with privacy-sensitive data and an understanding of relevant data governance and privacy considerations for identity data.

- Experience applying GenAI to boost developer/analytics productivity.

Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $330,000.00 - $566,000.00. This compensation range will vary based on location.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

Netflix is a unique culture and environment. Learn more here.

About Netflix

Netflix, Inc. is an American media company founded on August 29, 1997 by Reed Hastings and Marc Randolph in Scotts Valley, California, and currently based in Los Gatos, California, with production offices and stages at the Los Angeles-based Hollywood studios (formerly old Warner Brothers studios) and the Albuquerque Studios (formerly ABQ studios). It operates an eponymous over-the-top subscription video on-demand service, which showcases acquired and original programming as well as third-party content licensed from other production companies and distributors. Netflix is also the first streaming media company to be a member of the Motion Picture Association.
Learn more about Netflix
Size
11,300 employees
Market Cap
$127.6 billion
Industry
Net Income
$2.7 billion
Founded
1997
5 Year Trend
+27.5%
Revenue
$24.9 billion
NASDAQ

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