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Principal Data Scientist Jobs (NOW HIRING)

TradeStation Group, Inc.

Principal Data Scientist

The Principal Data Scientist will write clean, production-grade code, stay genuinely curious about emerging AI and ML techniques, and independently learn new tools before being asked to. The ...

Td

Principal Data Scientist (US)

Southfield, MI

$148K - $223K/yr

In addition, the Principal Data Scientist provides technical expertise with a focus on bank and industry-wide solutions that addresses capability gaps to create opportunities for significant value ...

Fidelity Investments

Principal Data Scientist

Boston, MA · On-site

$126K/yr

As a Principal Data Scientist, you will be a hands-on technical leader and mentor, guiding standard processes across NLP, speech analytics, and generative AI model development. You'll join a team ...

Cyod

Principal Data Scientist

Shelbyville, TN · On-site

$140 - $180/hr

Requisition Number: 105937 Principal Data Scientist Focus: Clinical / HLS, Google Cloud Gen AI, Agents, and Applied ML Location: Nashville, TN area preferred Insight at a Glance * 14,000+ engaged ...

TradeStation

Principal Data Scientist

The Principal Data Scientist will write clean, production-grade code, stay genuinely curious about emerging AI and ML techniques, and independently learn new tools before being asked to. The ...

Home Depot

Principal Data Scientist - CX

Atlanta, GA · On-site

The Principal Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the ...

Autodesk, Inc.

Principal Data Scientist

San Francisco, CA · On-site

$135K - $242K/yr

The Principal Data Scientist will work within an Engineering team focused on building frameworks to evaluate AI Systems. This is a critical data science role for our agentic product platform-a next ...

Home Depot

Principal Data Scientist, Online

Atlanta, GA · On-site

The Principal Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the ...

Formation Bio

Principal Data Scientist

New York, NY

$204K - $267K/yr

About the Position As a Principal Data Scientist at Formation Bio, you will be at the forefront of revolutionizing drug development through AI and advanced analytics. In this role, you'll lead ...

Menlo Ventures

Principal Data Scientist

California, MO · On-site

$200 - $260/hr

Databricks is looking for a Principal Data Scientist to serve as the statistical voice of the Data Science organization. This candidate will translate data science insights into clear, actionable ...

Autodesk

Principal Data Scientist

San Francisco, CA

$135K - $242K/yr

The Principal Data Scientist willwork within an Engineering team focused on buildingframeworksto evaluateAI Systems.This is acriticaldata science role for our agentic product platform-anext ...

Walmart

Principal, Data Scientist

Lowell, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Walmart

Principal, Data Scientist

Johnson, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Walmart

Principal, Data Scientist

Pea Ridge, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Leonardo DRS

Principal Data Scientist

Germantown, MD · On-site

$134K - $181K/yr

Join our radar defense team as a Principal Data Scientist and take a leading role in how we ensure data quality and validate the machine-learning models behind mission-critical systems. We are ...

Walmart

Principal, Data Scientist

Rogers, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Walmart

Principal, Data Scientist

Elkins, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Walmart

Principal, Data Scientist

Hoboken, NJ · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

Walmart

Principal, Data Scientist

Fayetteville, AR · On-site

$110K - $220K/yr

About the Role We are looking for a Principal Data Scientist to lead high-impact initiatives within Walmart's Decision Science organization. This role is centered on building scalable, end-to-end ...

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Principal Data Scientist information

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How much do principal data scientist jobs pay per year?

As of Aug 17, 2026, the average yearly pay for principal data scientist in the United States is $144,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,500.00 and $169,000.00 per year, depending on experience, location, and employer.

What is a principal data scientist?

Principal Data Scientists are senior-level professionals who lead data science projects and teams within an organization. They are responsible for designing and implementing complex analytical models to solve business problems, mentoring other data scientists, and setting strategic direction for data initiatives. Principal Data Scientists often collaborate with stakeholders to define project goals, interpret findings, and translate data insights into actionable recommendations. Their deep expertise in statistics, machine learning, and programming allows them to tackle high-impact challenges and drive innovation across the organization.

What are some typical challenges principal data scientists face when leading cross-functional data projects?

Principal Data Scientists often navigate challenges such as aligning diverse stakeholder expectations, managing project scope, and ensuring data quality across multiple sources. They are responsible for translating complex business needs into actionable data strategies while mentoring junior team members and fostering collaboration between data, engineering, and business teams. Balancing hands-on technical work with high-level project oversight and communication is key to driving impactful outcomes in this role.

What are the key skills and qualifications needed to thrive as a principal data scientist, and why are they important?

To thrive as a Principal Data Scientist, you need advanced expertise in statistics, machine learning, and data analysis, typically supported by a graduate degree in a quantitative field and extensive experience in data science roles. Proficiency with programming languages like Python or R, cloud platforms, big data tools (such as Spark or Hadoop), and experience with data visualization and ML frameworks are essential. Leadership, strategic thinking, and strong communication skills help you guide teams and translate complex analytics into actionable business insights. These skills ensure you can design impactful solutions, drive innovation, and deliver measurable value to organizations.

What is the difference between Principal Data Scientist vs Data Scientist?

AspectPrincipal Data ScientistData Scientist
Required CredentialsAdvanced degrees (Master's/PhD), extensive experienceBachelor's or Master's in related field
Work EnvironmentStrategic, leadership-focused, cross-team collaborationHands-on data analysis, model development
Employer & Industry UsageTech, finance, healthcare, large organizationsStartups, mid-sized companies, research roles

The Principal Data Scientist typically holds advanced degrees and extensive experience, focusing on strategic leadership and guiding data initiatives. Data Scientists are more involved in hands-on analysis and model building. While both roles require strong technical skills, the Principal Data Scientist operates at a higher strategic level within organizations.

How much does a principal data scientist make?

A principal data scientist typically earns between $120,000 and $180,000 annually, with total compensation often including bonuses and stock options. Salaries vary based on experience, industry, location, and company size, and advanced skills in machine learning and big data tools can influence pay levels.
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Principal Data Scientist jobs near you
Infographic showing various Principal Data Scientist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $144,009 per year, or $69.2 per hour.

Principal Data Scientist

TradeStation Group, Inc.

Remote

Full-time

PTO

Re-posted 7 days ago

Job description

#WeAreTradeStation
Remote Position - must reside in Florida, Texas, Illinois, New York, New Jersey, Colorado, Idaho, Massachusetts, Michigan, Minnesota, Missouri, North Carolina, South Carolina, Utah or Virginia
Who We Are:
TradeStation is the home of those born to trade. As an online brokerage firm and trading ecosystem, we are focused on delivering the ultimate trading experience for active traders and institutions. We continuously push the boundaries of what's possible, encourage out-of-the-box thinking, and relentlessly search for like-minded innovators.
At TradeStation, we are building an AI-First culture. We expect team members to embrace AI as a core part of their daily workflow, whether that's using AI to accelerate development, enhance decision-making, improve client outcomes, or streamline internal processes. We hire, grow, and promote people who can harness AI responsibly and creatively. We treat AI as a partner in problem-solving, not just a tool; following our governance standards to ensure AI is used ethically, securely, and transparently. If you join us, you're joining a culture where AI is how we work.
Are you ready to make yourself at home?
What We Are Looking For:
We're seeking a Principal Data Scientist to help design, build, and deploy advanced analytics and machine learning solutions that power TradeStation's trading platform, client experience, and business operations. Reporting to the Sr. Director of AI, Data Science & Enterprise Data, this role will own the full data science lifecycle - from exploratory analysis and model development through production deployment and ongoing monitoring.
This role is for a self-directed practitioner who thrives without hand holding. The ideal applicant will proactively identify opportunities where data science can create meaningful impact, build the solutions, and iterate rapidly. The Principal Data Scientist will write clean, production-grade code, stay genuinely curious about emerging AI and ML techniques, and independently learn new tools before being asked to. The applicant should be equally at home in a Jupyter notebook and a production ML pipeline.
This role will work closely with Product, Engineering, Compliance, and Analytics teams to build predictive models, behavioral analytics, and AI-powered capabilities that give TradeStation a competitive edge.
What You'll Be Doing:
Modeling & Machine Learning
  • Own the end-to-end ML lifecycle - from problem framing and feature engineering through model training, validation, deployment, and ongoing performance monitoring
  • Help build and deploy predictive models across a range of use cases including customer behavior, fraud and anomaly detection, trade surveillance, risk modeling, and personalization
  • Design and implement real-time and batch ML pipelines that operate reliably at scale in production environments
  • Develop behavioral anomaly detection and pattern recognition systems using statistical and deep learning approaches
  • Apply NLP and LLM techniques to extract insights from unstructured data - trade notes, client communications, market commentary, and internal documentation

Analytics & Visualization
  • Translate complex data into clear, compelling visualizations and narratives for both technical and executive audiences
  • Help design and build dashboards and analytical tools that empower stakeholders to make faster, more informed decisions
  • Conduct exploratory data analysis to surface trends, anomalies, and opportunities across trading behavior, customer segments, and platform performance
  • Define, track, and interpret key business and model performance metrics; proactively surface meaningful insights without waiting to be asked

AI Integration & Innovation
  • Stay at the forefront of AI and ML research - continuously evaluate and adopt emerging techniques (GenAI, RAG, agents, multimodal models) where they create real business value
  • Leverage AI tools (Claude, LLMs, foundation models) to accelerate your own development workflow, from code generation to documentation to data profiling
  • Experiment rapidly with new approaches; fail fast, iterate, and bring winning solutions to production
  • Contribute to TradeStation's AI governance standards by ensuring models are interpretable, fair, and deployed responsibly

Strategic Impact & Communication
  • Partner with Product and Engineering to define the data and modeling requirements for new platform features
  • Work with Compliance and Risk teams to build surveillance and monitoring systems that meet regulatory requirements
  • Communicate results and recommendations clearly to non-technical stakeholders; translate business questions into rigorous analytical frameworks

The Skills You Bring:
  • Self-Starter & Independent Learner -proactively identify problems worth solving, learn new techniques without being prompted, and drive projects to completion without needing direction
  • Full-Stack Data Science - proven ability to own the complete lifecycle: problem definition, data wrangling, feature engineering, modeling, deployment, and monitoring in production environments
  • Machine Learning Depth - strong command of supervised, unsupervised, and reinforcement learning methods; experience with time series, anomaly detection, NLP, and deep learning; know when to use simple models and when to go complex
  • Software Engineering Fundamentals - writes production-quality Python; comfortable with version control (Git), containerization (Docker), and MLOps best practices; code that others can maintain
  • Data Platform Proficiency - hands-on experience with Databricks, Spark, or Snowflake; able to write and optimize complex SQL; understands data modeling and pipeline design
  • Visualization & Storytelling - ability to build polished, insight-driven visualizations and dashboards (Tableau, Power BI, Plotly, Sigma); presents data science work in business terms
  • AI-Native Workflow - actively uses AI tools (Claude, Copilot, LLMs) in day-to-day work; has hands-on experience with LLM APIs, prompt engineering, or GenAI application development
  • Statistical Rigor - solid grounding in probability, statistics, and experimental design; applies A/B testing and causal inference correctly; doesn't overfit spurious signals
  • Cross-Functional Collaboration - comfortable working across Product, Engineering, Compliance, and Analytics; can present findings to executives and translate business requirements into analytical solutions
  • Financial Services Domain- experience with trading data, market microstructure, customer behavior in financial platforms, fraud detection, or regulatory compliance analytics strongly preferred
  • Experience building and monitoring ML models in production using MLflow, SageMaker, Vertex AI, or similar MLOps platforms preferred
  • Hands-on experience with LLM APIs, RAG architectures, or AI agent frameworks preferred
  • Track record of self-directed learning - personal projects, open-source contributions, Kaggle competition history, technical writing, or conference presentations preferred
  • Experience with fraud detection, behavioral anomaly detection, trade surveillance, or risk modeling in financial services preferred
  • Familiarity with real-time streaming data (Kafka, Spark Streaming) and low-latency model serving preferred
  • Experience with cloud ML infrastructure (Azure, AWS, or GCP) and distributed computing preferred

Minimum Qualifications:
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
  • 7+ years of experience in data science or applied machine learning roles, with demonstrated ownership of models deployed to production

Desired Qualifications:
  • Master's or PhD in a quantitative discipline

What We Offer:
  • Collaborative work environment
  • Competitive Salaries
  • Yearly bonus
  • Comprehensive benefits for you and your family starting Day 1
  • Unlimited Paid Time Off
  • Flexible working environment
  • TradeStation Account employee benefits, as well as full access to trading education materials
  • Pay Range (US) $140-180K (Countries outside of the US have differing ranges in accordance with local labor markets)

TradeStation provides equal employment opportunities to current and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, sexual orientation, age, pregnancy, disability, handicap, citizenship, veteran or marital status, or any other legally recognized status entitled to protection under federal, state, or local anti-discrimination laws.
#LI-Remote

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