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Data Science Trading Jobs (NOW HIRING)

Swish Analytics

Data Scientist

San Francisco, CA · On-site +1

$150K/yr

This role will work at the intersection of data science, trading, and data engineering to help develop and maintain trader automation algorithms that will react faster to signals as well as improve ...

Swish Analytics

Data Scientist

San Francisco, CA · Remote

$150K/yr

This role will work at the intersection of data science, trading, and data engineering to help develop and maintain trader automation algorithms that will react faster to signals as well as improve ...

Next Step Systems

Data Science Developer

Chicago, IL · On-site

Data Science Developer, Chicago, IL We are seeking a talented Data Science Developer candidate to ... Responsibilities: - Develop processes to collect and analyze data for automated trading systems ...

FanDuel

Data Science Manager

Jersey City, NJ · On-site

You will be working closely with the product and risk and trading teams, modeling player ... This role will also manage and develop other data scientists. You will promote effective ...

FanDuel

Data Science Manager

Manhattan, NY · On-site

$149 - $186/hr

You will be working closely with the product and risk and trading teams, modeling player ... This role will also manage and develop other data scientists. You will promote effective ...

FanDuel

Data Science Manager

Jersey City, NJ · On-site

You will be working closely with the product and risk and trading teams, modeling player ... This role will also manage and develop other data scientists. You will promote effective ...

FanDuel

Data Science Manager

Jersey City, NJ

You will be working closely with the product and risk and trading teams, modeling player ... This role will also manage and develop other data scientists. You will promote effective ...

SageSure

Director Data Science

Jersey City, NJ

In this role, you will lead a team of data scientists in solving some of the most complex and high ... Influence and align stakeholders by articulating clear priorities, trade-offs, and expected ...

Totalwine

This role will lead multiple data science team members with a significant portfolio of initiatives ... Ability to make informed trade-offs across modeling approaches, data pipelines, tooling, and ...

Total Wine & More

Director, Data Science

Bethesda, MD · On-site

This role will lead multiple data science team members with a significant portfolio of initiatives ... Ability to make informed trade-offs across modeling approaches, data pipelines, tooling, and ...

SageSure

Director Data Science

Jersey City, NJ · On-site

In this role, you will lead a team of data scientists in solving some of the most complex and high ... Influence and align stakeholders by articulating clear priorities, trade-offs, and expected ...

Rock Connections

Manager, Data Science

$128K - $276K/yr

As the Manager, Data Science, you'll lead a team of data scientists as they apply data science to ... Today, we're a publicly traded company involved in many different industries, including mortgages ...

TBK Bank, SSB

Director of Data Science

Dallas, TX

Director Of Data Science At Triumph, our vision is a world where freight transactions are accurate ... operational trade-offs. * Lead signal development for transportation intelligence products ...

Walmart

(USA) Director, Data Science

Tontitown, AR · On-site

$130K - $260K/yr

The (USA) Director, Data Science leads the development and execution of advanced data science ... By evaluating trade-offs, interactions, and constraints, the team recommends coordinated actions ...

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Data Science Trading information

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$24K

$115.8K

$211K

How much do data science trading jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data science trading in the United States is $115,802.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,000.00 and $159,000.00 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.
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Data Science Trading jobs near you
Infographic showing various Data Science Trading job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $115,802 per year, or $55.7 per hour.

Data Scientist

Swish Analytics

San Francisco, CA • On-site, Remote

$150K/yr

Full-time

Re-posted 19 days ago

Job description

Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Job Description
You'll be joining a team that is working to develop the infrastructure for a system to optimize our simulation outputs based on a variety of external and internal signals. This role will work at the intersection of data science, trading, and data engineering to help develop and maintain trader automation algorithms that will react faster to signals as well as improve model accuracy. This position is remote from the USA or Canada.
Duties:
  • Develop infrastructure for trader automation and system performance tracking
  • Develop high-performance and low-latency products to react to external and internal signals
  • Analysis of live-streaming data and turning it into actionable decisions
  • Design and set up tests to detect unexpected changes to our models resulting from manual interactions.
  • Use extensive experience to build, test, debug, and deploy production-grade components
  • Ideate, develop, and improve machine learning and statistical models that drive Swish's core algorithms, growing into top-level simulation output modeling as we expand to new sports.
  • Develop contextualized feature sets that draw on sports-specific domain knowledge.
  • Contribute across all stages of model development - from proof-of-concept and beta testing to partnering with data engineering and product teams to deploy new models.
  • Constantly improve model performance using insights from rigorous experimentation.
  • Assess model performance, identify weaknesses, and use those findings to direct development efforts.
  • Document your work and present it clearly to technical and non-technical partners.

Requirements
  • Bachelor's in Data Science, Statistics, Computer Science, Applied Math, or a related technical field; Master's strongly preferred.
  • 4+ years developing and delivering effective machine learning and/or statistical models to serve real business needs in sports analytics or sports betting.
  • Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods.
  • Excellent analytical and problem-solving ability, and a demonstrated drive to learn quickly in unfamiliar territory.
  • Experience with Python and relational SQL.
  • Strong foundation with source control (GitHub) and related CI/CD processes.
  • Strong foundation working in AWS environments.
  • Ideal candidates will have experience with Kafka, Docker, and Kubernetes
  • Ability to partner across teams on complex, ambiguous problems and communicate clearly with technical and non-technical audiences.

Base salary: Starting at $150,000 - DOE
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to those outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote

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