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Data Science Trading Jobs (NOW HIRING)

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DATA ENGINEER - DATA SCIENCE TEAM

Newport News, VA · Hybrid

$104K - $131K/yr

DATA ENGINEER - DATA SCIENCE TEAM Location: Newport News, Virginia, United States Date: Jun 27 ... Our diverse and innovative team of professionals ranges from skilled trades to project managers ...

FanDuel

Risk Data Science, Director

Jersey City, NJ

... Data Science Director to help shape our Risk & Trading team at America's #1 Sportsbook. The role ... You will be a key member of the Risk & Trading leadership team , partnering closely with Trading ...

Fidelity Investments

Director, Data Science

Boston, MA · On-site

$126K/yr

The Role This is an individual contributor data science role.In this role, the individual leads ... We partner with investment professionals, portfolio managers, analysts, quants, traders, and other ...

Fidelity Investments

Director, Data Science

Boston, MA · On-site

$126K/yr

The Role This is an individual contributor data science role. In this role, the individual leads ... We partner with investment professionals, portfolio managers, analysts, quants, traders, and other ...

Vitol

Software Engineer in Data Science

Houston, TX · On-site

$109K - $131K/yr

Vitol is the world's largest independent energy and commodities trading company, and they are seeking an experienced Software Engineer to join their global data science and machine learning team. The ...

S&P Global, Inc.

Vice President, Data Science

New York, NY · On-site

$177K - $350K/yr

We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor ... trade-offs, and failure modes. * Experience operating models in production over time, including ...

Spgi

Vice President, Data Science

Raleigh, NC · On-site

$177K - $350K/yr

We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor ... trade-offs, and failure modes. * Experience operating models in production over time, including ...

S&P Global

Vice President, Data Science

New York, NY · On-site

$177K - $350K/yr

We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor ... trade-offs, and failure modes. * Experience operating models in production over time, including ...

S&P Global

Vice President, Data Science

Raleigh, NC · On-site

$177K - $350K/yr

We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor ... trade-offs, and failure modes. * Experience operating models in production over time, including ...

Spgi

Vice President, Data Science

New York, NY · On-site

$177K - $350K/yr

We are seeking a Data Scientist Leader to lead the design, development, and operation of high-rigor ... trade-offs, and failure modes. * Experience operating models in production over time, including ...

Blend360

Marketing Data Science Manager

Columbia, MD · On-site

$125K - $160K/yr

Translate business needs into actionable data science solutions, evaluating multiple approaches and clearly communicating trade-offs. * Collaborate with stakeholders to align on methodology ...

Blend360

Marketing Data Science Manager

Columbia, MD

$125K - $160K/yr

Translate business needs into actionable data science solutions, evaluating multiple approaches and clearly communicating trade-offs. * Collaborate with stakeholders to align on methodology ...

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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 Jul 4, 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 the 80 20 rule in data science?

In data science trading, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or strategies to optimize model performance and decision-making.

What are the key skills and qualifications needed to thrive in the Data Science Trading position, and why are they important?

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.

Can a data scientist become a quant trader?

A data scientist can become a quant trader by applying skills in statistical analysis, programming, and machine learning to develop trading algorithms. Transitioning often requires understanding financial markets, risk management, and familiarity with tools like Python, R, and trading platforms. Additional certifications or experience in finance can facilitate this career shift.

What is a Data Science Trading job?

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 are some typical responsibilities and daily tasks for professionals working in Data Science Trading?

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.

Is data science useful for trading?

Data science is highly useful for trading, as it enables analysts and traders to develop predictive models, identify market patterns, and make data-driven decisions. Skills in machine learning, statistical analysis, and programming tools like Python or R are often essential in this field.

Is 40 too late for data science?

Data science trading roles are open to candidates of all ages, and many professionals transition into data science later in their careers. Success depends on skills, experience, and continuous learning, such as mastering programming languages like Python or R and understanding financial markets. Age is less a barrier than relevant expertise and adaptability.
More about Data Science Trading jobs
What cities are hiring for Data Science Trading jobs? Cities with the most Data Science Trading job openings:
What are the most commonly searched types of Data Science Trading jobs? The most popular types of Data Science Trading jobs are:
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Data Science Trading jobs near you
Infographic showing various Data Science Trading job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 2% As Needed, 10% Full Time, 65% Part Time, and 22% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $115,802 per year, or $55.7 per hour.
Director - Data Science Consulting

Director - Data Science Consulting

Tiger Analytics Inc.

California City, CA

Full-time

Posted 28 days ago

Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for an Director of Data Science to lead high-impact applied ML and analytics initiatives. This role combines deep technical expertise, strong experimentation rigor, and business leadership to influence product direction and drive measurable outcomes at scale.

Responsibilities:

  • Own and drive end-to-end data science workstreams from problem definition to production and impact measurement.
  • Build and scale statistical and ML models for personalization, recommendations, growth optimization, fraud, and experimentation platforms.
  • Partner closely with Product, Engineering, Marketing, and Leadership to define success metrics, trade-offs, and roadmaps.
  • Design and maintain production ML pipelines using Python, SQL, Airflow, and modern data tooling.
  • Collaborate with client stakeholders to translate business needs into high-level analytical solution designs.
  • Present insights and solutions to business leaders, demonstrating impact and value.
  • Manage analytics projects and coordinate with global client and Tiger teams.
  • Lead requirement discussions, and oversee planning, development, and documentation of DS/AI solutions.
  • Partner with technical teams to select appropriate analytical methods and generate actionable insights.
  • Communicate results to senior leadership and support the operationalization of analytics solutions.

Requirements

  • 15+ years of professional experience in Data Science, Applied ML, or Advanced Analytics, with leadership at scale..
  • Must have experience working on traditional ML Models. Knowledge of ML frameworks like Scikitlearn, Tensorflow, and Keras.
  • Strong hands-on expertise in Python, SQL, and statistical modeling.
  • Familiarity with data orchestration and workflows (Airflow, Git-based CI/CD, Fivetran).
  • Strong understanding of cloud-native data and ML platforms (AWS, GCP, Azure).
  • Excellent communication skills with the ability to influence Director+ stakeholders.
  • Identify and implement improvements to analytics workflows and processes to enhance efficiency and effectiveness.
  • Ensure all analytical activities adhere to guidelines, regulatory requirements, and industry standards.
  • Ability to engage with executive/VP-level stakeholders from the client's team to translate business problems into high-level analytics solution approaches.
  • A solid understanding of statistical and machine-learning algorithms is a plus.
  • Bachelor's in Business Analytics or equivalent work experience.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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