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Algorithm Scientist Jobs in New York, NY (NOW HIRING)

Collaborate with scientists and researchers in various areas to develop state-of-the-art algorithms, software, and computer systems solutions to challenging problems. * Assess the requirements for ...

You love building mathematical and probabilistic models, computer science algorithms, and you have exposure to (multi-terabyte) big data Qualifications Implementation experience with supervised and ...

You love building mathematical and probabilistic models, computer science algorithms, and you have exposure to (multi-terabyte) big data Qualifications Implementation experience with supervised and ...

Collaborate with scientists and researchers in various areas to develop state-of-the-art algorithms, software, and computer systems solutions to challenging problems. * Assess the requirements for ...

Collaborate with scientists and researchers in various areas to develop state-of-the-art algorithms, software, and computer systems solutions to challenging problems. * Assess the requirements for ...

Their algorithms sit at the core of the product -- solving complex optimisation problems that ... Bachelor's degree in Computer Science, Mathematics, Operations Research, Financial Engineering, or ...

AI Scientist

New York, NY · Hybrid

$150K - $200K/yr

We are seeking an exceptionally talented AI Scientist to join the Artificial Intelligence team at ... Implement state of the art machine learning algorithms * Design deep learning architectures.

Garner is hiring Applied Scientists to design and ship the algorithmic systems at the core of our product. Our members rely on us to answer hard questions - Which doctor should I see? What will it ...

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Algorithm Scientist information

See New York, NY salary details

$55.2K

$121.8K

$150.4K

How much do algorithm scientist jobs pay per year?

As of Sep 9, 2026, the average yearly pay for algorithm scientist in New York, NY is $121,813.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $149,900.00 per year, depending on experience, location, and employer.

What is an algorithm scientist?

Algorithm Scientists are professionals who design, analyze, and optimize algorithms to solve complex computational problems. They often work in fields like data science, artificial intelligence, finance, and engineering, developing new methods or improving existing ones for processing data efficiently. Their work involves rigorous mathematics, computer science, and research to ensure algorithms are accurate, scalable, and effective for specific applications. Algorithm Scientists may also collaborate with software engineers to implement their solutions in real-world systems.

How does an algorithm scientist typically collaborate with cross-functional teams during the development process?

Algorithm Scientists frequently work alongside data engineers, software developers, and product managers to design and implement solutions. They are often responsible for communicating complex mathematical concepts in accessible terms to ensure alignment across the team. Regular meetings and code reviews are common, allowing for feedback and rapid iteration. This collaborative environment helps ensure that the algorithms developed are both technically sound and practically viable for real-world applications.

What are the key skills and qualifications needed to thrive as an algorithm scientist, and why are they important?

To thrive as an Algorithm Scientist, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree such as a Master's or Ph.D. in a related field. Proficiency with programming languages like Python or C++, machine learning libraries (e.g., TensorFlow, PyTorch), and experience with data analysis tools are typically required. Strong problem-solving abilities, analytical thinking, and effective communication skills help distinguish top performers in this role. These skills are vital for developing innovative algorithms that solve complex problems, ensuring practical, scalable solutions in technological environments.

What cities near New York, NY are hiring for Algorithm Scientist jobs?

Cities near New York, NY with the most Algorithm Scientist job openings:

Infographic showing various Algorithm Scientist job openings in New York, NY as of June 2026, with employment types broken down into 1% Locum Tenens, 90% Full Time, 8% Part Time, and 1% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $121,813 per year, or $58.6 per hour.

Data Scientist, Algorithms - Lyft Ads

Manhattan, NY • On-site

SupportFinity™
IT Services • 51 - 200 employees

$125 - $150/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 21 days ago


Key responsibilities

  • Design, develop, and deploy production‑grade machine learning models and algorithms for Lyft Ads capabilities.

  • Own the end‑to‑end lifecycle of modeling projects, including problem definition, data exploration, feature engineering, model development, deployment, and monitoring.

  • Collaborate with Engineering to integrate models into real‑time ad‑serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.


Job description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Lyft Ads is one of Lyft’s newest and fastest-growing businesses, focused on building the world’s largest transportation media network. Our mission is to help brands reach riders during key moments of their journey—before, during, and after a ride—by delivering meaningful, contextually relevant ad experiences. We operate at the intersection of mobility data, real-time decision systems, and AI-powered personalization, enabling advertisers to run high-impact campaigns with measurable outcomes.

Algorithms Scientist to help build the next generation of ads relevance, targeting, optimization, and measurement algorithms that power the Lyft Ads platform. In this role, you will work across large-scale datasets and complex real-time systems to design, prototype, and deploy production-grade machine learning models. You’ll collaborate closely with Engineering, Product, Data Science, and Sales to translate ambiguous business and advertiser needs into rigorous algorithmic solutions that improve ad performance, enhance marketplace efficiency, and drive meaningful revenue growth.

This is a high-impact, highly technical role within a rapidly scaling business line. The ideal candidate brings strong applied machine learning intuition, hands‑on modeling experience, and the ability to write clean, efficient production code. You will play a critical role in shaping how advertisers connect with Lyft riders—pushing the boundaries of personalization, measurement, and real‑time optimization in a dynamic marketplace.

Lyft highly values having employees working in‑office to foster a collaborative work environment and company culture. This role will be in‑office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in‑office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.

The expected base pay range for this position in the New York City area is $128,000 - $160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Responsibilities
  • Design, develop, and deploy production‑grade machine learning models and algorithms that power core Lyft Ads capabilities, such as ad relevance, targeting, ranking, bid optimization, pacing, campaign delivery, and measurement.
  • Own the end‑to‑end lifecycle of modeling projects — including problem definition, data exploration, feature engineering, model development, offline evaluation, deployment, and monitoring.
  • Collaborate closely with Ads Engineering to integrate models into real‑time ad‑serving and batch decision systems, ensuring performance across latency, scalability, and reliability constraints.
  • Analyze large‑scale mobility, behavioral, and ads performance datasets to identify patterns, surface opportunities, and guide ML and AI driven product improvements.
  • Implement rigorous model evaluation frameworks, including offline metrics, statistical tests, calibration, sensitivity analysis, and A/B experimentation to validate both model impact and system‑level outcomes.
  • Build robust training pipelines, feature transformations, and scoring infrastructure, ensuring reproducibility, observability, and long‑term maintainability.
  • Partner with Product, Engineering, and Sales to translate ambiguous advertiser goals (e.g., increased conversions, reach efficiency, brand lift) into measurable requirements and success metrics.
  • Investigate and resolve model behavior issues, production regressions, calibration drift, and performance anomalies in close partnership with Ads Infra teams.
  • Drive innovation by staying current with advances in ML for ranking, recommendation, causal inference, optimization, and ads measurement — and proactively identifying opportunities to apply them.
  • Contribute to Lyft Ads’ modeling and experimentation infrastructure, through model cards, documentation, reproducibility standards, and code quality improvements.
Experience
  • Master’s, or PhD in Machine Learning, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative fields; or equivalent applied industry experience.
  • 3–5 years of hands‑on ML/applied science experience, ideally involving production models, large‑scale systems, or ads/recommendation/relevance domains. Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, JAX, or scikit‑learn; ability to write clean, efficient, production‑adjacent code.
  • Experience working with large‑scale datasets and distributed data tools (Spark, Snowflake, Presto, Databricks).
  • Practical experience building and evaluating:
    • Ranking and relevance models
    • Optimization or pacing algorithms
    • Predictive models for CTR, CVR, or user response
    • Causal or experimentation‑based measurement methods
  • Understanding of online/offline evaluation techniques, including:
    • Offline metrics (AUC, NDCG, MRR, calibration)
    • A/B testing methodologies
    • Bias correction and counterfactual estimation
  • Ability to solve ambiguous problems by structuring analyses, evaluating trade‑offs, and proposing algorithmic solutions grounded in scientific rigor.
  • Strong communication skills, with an ability to clearly explain model behavior, constraints, trade‑offs, and recommendations to engineering, product, and sales partners.
  • Demonstrated ownership of modeling work, including debugging, monitoring, documentation, and iteration after deployment.
  • Curiosity, initiative, and a track record of delivering measurable improvements through high‑quality modeling.
Benefits
  • Great medical, dental, and vision insurance options with additional programs available when enrolled
  • Mental health benefits
  • Family building benefits
  • Child care and pet benefits
  • 401(k) plan to help save for your future
  • In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
  • Subsidized commuter benefits
  • Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

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