ZipRecruiter

Log In

1

Data Science Trading Jobs in New York (NOW HIRING)

Hudson River Trading

Data Production Engineer

New York, NY · On-site

$125K - $150K/yr

You thrive in the fast-paced environment of a daily live trading operation Qualifications * 2+ years of experience in a data engineering/science role OR a degree in data science or a similar ...

PayPal

Sr Data Scientist

New York, NY · On-site

$143K - $212K/yr

... trade. Our beliefs are the foundation for how we conduct business every day. We live each day ... Drive best practices in data science. * Ensure data quality and integrity in all processes.

Talanto

Data Scientist, Market Making

Jersey City, NJ · On-site

$125 - $150/hr

Working closely with algorithmic traders, quant engineers, and product teams, you will translate ... Experience in data science, analytics, quantitative research, or engineering preferred * Bachelor ...

Posted today

Unchain Data

Director, Data Analytics

Manhattan, NY · On-site

$200 - $250/hr

We're growing quickly, both in terms of volume ($115B traded to date) and adoption as an ... You'll lead our embedded analytics organization, including analysts and data scientists aligned to ...

Compass

Lead Data Scientist

Manhattan, NY · On-site

$150 - $200/hr

You will set the standard for data science excellence, architect scalable solutions, and help ... Synthesize and communicate highly complex methodologies, technical trade-offs, and strategic ...

Compass

Lead Data Scientist

New York, NY · On-site

$175K - $195K/yr

You will set the standard for data science excellence, architect scalable solutions, and help ... Synthesize and communicate highly complex methodologies, technical trade-offs, and strategic ...

SupportFinity™

Data Scientist (Product)

Manhattan, NY · On-site

$150 - $200/hr

We're looking for a dedicated and ambitious data science leader to help us accelerate product ... Your work will directly influence the roadmap, uncover new opportunities, and improve the trading ...

Unchain Data

Data Scientist Markets

Manhattan, NY · On-site

$150 - $200/hr

We enable individuals to express views on real-world events by trading on outcomes across politics ... This role sits inside that team as the dedicated data scientist, owning the analytical layer that ...

AQR

2027 Trading Analyst

Greenwich, CT

$145K - $155K/yr

They enjoy testing hypotheses and using data science to solve real-world trading and investment problems. Whether through programming, AI-assisted tools, or other analytical approaches, they are ...

previous page

Showing results 41-60

All JobsData Science Trading JobsData Science Trading Jobs in New York

Data Science Trading information

See New York salary details

$26.2K

$126.6K

$230.7K

How much do data science trading jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data science trading in New York is $126,603.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,876.00 and $173,830.00 per year, depending on experience, location, and employer.

What is a data science trading?

A Data Science Trading job involves using data analysis, machine learning, and statistical modeling to develop trading strategies and optimize financial decision-making. Professionals in this field work with large datasets, build predictive models, and implement algorithms to identify market patterns and trading opportunities. They collaborate with traders and quantitative analysts to enhance trading performance and manage risk. Strong programming skills in Python, R, or SQL, along with expertise in finance and mathematics, are essential for success in this role.

What does a data science trading do?

Data Science Trading professionals typically analyze large financial datasets, develop algorithmic trading models, and monitor the performance of existing strategies. A typical day might include collaborating with traders and engineers, implementing new statistical techniques or machine learning algorithms, and backtesting strategies against historical market data. Routine tasks also involve writing code to automate processes, conducting risk assessments, and presenting insights to stakeholders. This role is highly collaborative and requires adapting to rapidly changing market conditions, making each day dynamic and intellectually challenging.

What are the key skills and qualifications needed to thrive in data science trading?

To thrive in Data Science Trading, you need strong quantitative analysis, statistical modeling, and programming skills, usually supported by a degree in a quantitative field like mathematics, finance, or computer science. Proficiency in Python, R, SQL, and experience with machine learning frameworks and trading platforms such as Bloomberg or QuantConnect are commonly required. Excellent problem-solving, collaboration, and the ability to communicate complex concepts clearly are standout soft skills. These capabilities are crucial for building, optimizing, and explaining data-driven trading strategies in fast-paced financial environments.

Is data science good for trading?

Data science is valuable in trading roles for analyzing large datasets, developing predictive models, and automating decision-making processes. Skills in programming, statistics, and machine learning are essential, and professionals often use tools like Python, R, and SQL to support trading strategies.

What are the most commonly searched types of Data Science Trading jobs in New York?

The most popular types of Data Science Trading jobs in New York are:

What are popular job titles related to Data Science Trading jobs in New York?

For Data Science Trading jobs in New York, the most frequently searched job titles are:

What job categories do people searching Data Science Trading jobs in New York look for?

The top searched job categories for Data Science Trading jobs in New York are:

What cities in New York are hiring for Data Science Trading jobs?

Cities in New York with the most Data Science Trading job openings:

Data Science Trading jobs near you
Infographic showing various Data Science Trading job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $126,603 per year, or $60.9 per hour.

Data Scientist - Blockchain Intelligence

Merkle Science

New York, NY • On-site

Full-time

Medical

Re-posted 24 days ago

Job description

About Merkle Science
Merkle Science provides blockchain transaction monitoring and intelligence solutions for web3 companies, digital asset service providers, financial institutions, law enforcement and government agencies to detect, investigate, and prevent illicit use of cryptocurrencies. Our vision is to make cryptocurrencies safe and provide infrastructure for the safe and compliant growth of cryptocurrencies.

Merkle Science is headquartered in New York with offices in Singapore, Bangalore and London. The team has combined experience across Bank of America, Paypal, Luno, Thomson Reuters and Amazon. The company has raised over $27M from SIG, Beco, Republic, DCG, Kenetic, GGV and several others.

About the role

We turn raw on-chain activity into trustworthy intelligence - clustering addresses into real-world entities, attributing them to services and actors, and surfacing risk for compliance and investigations teams. We're looking for a data scientist who is as comfortable shipping a heuristic to production as they are designing it: someone who can move from a messy hypothesis to a working pipeline without waiting on someone else to wire up the data.


You'll work closely with our attribution and clustering leads on models and heuristics that run across billions of transactions and multiple chains (Bitcoin, Ethereum, Tron, Solana, and more).

What you'll do

  • Design, test, and ship clustering and attribution heuristics, and measure them with real precision/coverage metrics rather than vibes.

  • Own your data end to end - pull, clean, join, and model large on-chain datasets without depending on a separate team for every query.

  • Build and maintain the pipelines that take a heuristic from notebook to production, including backfills, incremental runs, and validation.

  • Investigate edge cases (mixers, bridges, exchange hot wallets, consolidation patterns) and translate findings into repeatable logic.

  • Partner with investigations and product to define what "correct" looks like and benchmark against ground truth.

  • Prototype quickly, then harden what works.

What we're looking for

  • 4+ years building data science or data engineering systems that actually shipped (not just notebooks).

  • Strong Python and SQL; comfortable with large datasets and the gotchas of joins, dedup, and skew at scale.

  • Solid grasp of clustering, graph/network analysis, or entity resolution - and a habit of validating results, not just producing them.

  • Ability to reason about precision vs. coverage trade-offs and defend your metrics.

  • Self-directed: you can scope an ambiguous problem, get the data yourself, and drive it to a result.

Our tech stack

You don't need to have used all of these, but here's what you'd be working with day to day:


  • Databricks - our lakehouse and processing backbone. Large-scale on-chain datasets are transformed and modeled here via Spark and SQL; most heuristics run as Databricks jobs against billions of transactions.

  • Kafka - real-time ingestion of on-chain and transaction data. New blocks and events stream in continuously, so a lot of our work is designed to run incrementally rather than as one-off batch jobs.

  • Python - the primary language for everything from exploratory analysis to production heuristics and pipeline code.

  • TigerGraph - our graph database, where addresses, transactions, and entities live as a network. Clustering, traversals, and relationship queries (who funds whom, consolidation paths, entity linkage) happen here.


Supporting cast you'll likely touch:


  • SQL everywhere - for ad-hoc analysis, validation, and defining ground-truth datasets.

  • Columnar / analytical stores (e.g., ClickHouse) for fast aggregate queries over large tables.

  • Orchestration & scheduling for backfills and recurring pipeline runs.

  • Git / GitHub for version control and code review - we expect pipelines and heuristics to be reviewed like any other code.

  • GCP as our cloud environment.

How we work

Small, high-trust team. You'll have a lot of ownership and very little bureaucracy. We prototype fast, measure honestly, and ship.


Well Being, Compensation and Benefits
We care about your well-being. Along with excellent health insurance, we offer flexible time off, learning & development initiatives and hours that are designed to provide work/life balance.  We regularly host team-building sessions and encourage discussions around mental health.  

We reward talent and believe in acknowledging people for their contributions.  We offer industry-leading compensation, along with generous equity.  As a rapidly growing business, there are endless opportunities to grow your career with Merkle Science.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job

Apply