Senior Data Scientist

Shamrock Trading Corporation; Overland Park (KS); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Training and Development

Healthcare premiums for employees and/

401(k) contributions and ESOP after 1y

PTO & volunteering opportunities

Job summary

Shamrock Trading Corporation is seeking a Data Scientist to join our team with a focus on fraud detection and risk assessment across our factoring, payments, lending, and freight marketplace businesses.

Data Scientists partner closely with business stakeholders, analysts, and Machine Learning Engineers to explore data, build and evaluate models, and communicate findings that drive efficiency, enable risk management, and support strategic objectives.

Qualifications

• Experience with relational databases and SQL.
• Experience using statistical languages (Python, R, etc.).
• Knowledge of data platforms or cloud environments (Databricks, AWS).
• Experience using Git and collaborative workflows.
• Experience applying statistical techniques to real-world business problems.

Responsibilities

• Translate fraud, risk, and credit questions into analytical and modeling approaches.
• Analyze invoice, funding, payment, carrier, debtor, customer data to identify risk patterns.
• Develop and evaluate analytical and machine learning models for fraud detection and risk scoring.
• Define risk signals, thresholds, and evaluation criteria with stakeholders.
• Coordinate with ML team to deploy models into production.
• Connect fraud initiatives with reporting and performance metrics.
• Document assumptions and model limitations for transparent decisions.
• Stay current on fraud patterns and risk approaches across domains.

Skills

SQL

Python

R

Statistical modeling

Data visualization

Problem solving

Business acumen

Communication

Curiosity to learn

Education

Bachelor’s degree in a quantitative field (Statistics, Data Science, Analytics, Computer Science, Applied Mathematics, Engineering)

Tools

Databricks

AWS

Git

Power BI

Tableau

Job description

About Shamrock Trading Corporation

Shamrock Trading Corporation is a family of brands that has been serving the transportation and logistics industries since 1986. Shamrock offers factoring solutions, export financing, third-party logistics, a fuel card program and trucking technology.

Shamrock’s mission since the start has been to create value and success for our customers, our partners and our people. Strong ethics, dedication to our customers and close attention to the marketplace are critical to the success and growth of the Shamrock brands. Shamrock is headquartered in Overland Park, Kansas, with multiple offices throughout the U.S. Overland Park is a great place to live, work and play, being conveniently located within driving distance of everything Kansas City has to offer. Housed within the heart of Overland Park, our offices include 4 gorgeous towers on the East and West sides of Metcalf Ave. With a heavy community presence and a winning culture, Shamrock is a great place to work in Overland Park!

Why You’ll Love Working Here

Our award‑winning culture is a testament to our commitment to growth, recognition and empowerment. From day one, we prioritize employees first, encouraging them to think and act like owners and providing endless opportunities for growth and self‑development, both personally and professionally. Shamrock has been recognized as one of America’s 2025 “Most Loved Workplaces” by Newsweek.

Benefits

• Training and Development: Ongoing training and professional development opportunities
• Medical: Fully paid healthcare, dental and vision premiums for employees and eligible dependents, and gym benefits
• Financial: Generous company 401(k) contributions and employee stock ownership after one year
• Work‑Life Balance: Competitive PTO and fully paid time off opportunities to volunteer within your community

About The Role

Shamrock Trading Corporation is looking for a Data Scientist to join our team with a focus on fraud detection and risk assessment across our factoring, payments, lending, and freight marketplace businesses. Data Scientists partner closely with business stakeholders, analysts, and Machine Learning Engineers to explore data, build and evaluate models, and communicate findings that drive efficiency, enable risk management, and support strategic objectives.

This role will apply statistical, analytical, and machine learning techniques to help Shamrock better identify suspicious behavior, reduce financial loss, improve risk decisioning, and support faster, more confident customer funding decisions. The Data Scientist will work closely with Product, Credit, Risk, Operations, Data Services, Machine Learning Engineers, and business stakeholders to understand fraud patterns, build risk signals, evaluate models, and translate findings into practical business action.

This role is well‑suited for a data scientist or advanced analytics professional with experience in fraud, risk, credit, marketplace abuse, payments, lending, logistics, or identity verification who wants to apply those skills to complex real‑world problems in freight and financial services.

What You’ll Do

• Translate fraud, risk, and credit questions into analytical and modeling approaches
• Analyze invoice, funding, payment, carrier, debtor, customer, behavioral, and operational data to identify risk patterns and emerging fraud trends
• Develop and evaluate analytical and machine learning models to support fraud detection, risk scoring, anomaly detection, and early warning indicators
• Partner with Product, Credit, Risk, Audit, Operations, and business stakeholders to define risk signals, success metrics, decision thresholds, and model evaluation criteria
• Coordinate with Machine Learning team to transfer custom models into production deployments and platform integrations
• Partner with Data Analysts and BI teams to connect fraud and risk initiatives with reporting, monitoring, and business performance metrics
• Document assumptions, methodologies, data limitations, model performance, and findings to support transparent decision‑making
• Stay current on fraud patterns and risk approaches across factoring, freight, logistics, payments, lending, and marketplace businesses

Requirements

• Bachelor’s degree in a quantitative field (Statistics, Data Science, Analytics, Computer Science, Applied Mathematics, Engineering), or equivalent practical experience
• Experience with relational databases and SQL
• Experience using statistical programming languages (Python, R, etc.)
• Knowledge of modern data platforms or cloud environments (Databricks, AWS, etc.)
• Experience using Git and collaborative development workflows
• Experience applying statistical or analytical techniques to real‑world business problems (regression, classification, distributions, optimization, etc.)
• Experience visualizing/presenting data for stakeholders (Power BI, Tableau, etc.)
• Strong analytical thinking, problem‑solving skills, and curiosity about business, fraud, and risk drivers
• A drive to learn new technologies, fraud patterns, risk techniques, and industry context

Preferred

• Experience in fraud analytics, risk analytics, credit risk, underwriting, payments fraud, marketplace fraud, identity verification, logistics, freight brokerage, factoring, asset‑based lending, SMB lending, commercial lending, or financial services
• Experience building or supporting fraud detection, anomaly detection, risk scoring, credit scoring, identity risk, or transaction monitoring models
• Experience working with adversarial risk problems where bad actors change behavior in response to controls
• Experience with entity resolution, graph analytics, network analysis, behavioral analytics, or relationship‑based risk detection
• Experience working with invoice, payment, bank account, carrier, debtor, customer, document, device, or transaction‑level data
• Experience partnering with Product, Engineering, Operations, Credit, Risk, or Compliance teams to move analytical work into business processes or production systems

Apply Today!

We’re so excited to connect with you! If you want to work with forward‑thinking people in an award‑winning culture, submit your application today.

Having trouble submitting your application? Contact us at [e-mail] for support.