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Credit Risk Data Science Jobs in Sugar Land, TX (NOW HIRING)

East West Bank

Financial Crimes Data Scientist

Houston, TX · On-site

$100 - $200/hr

Develop risk-scoring, anomaly detection, predictive, and network analytics models using internal ... Hands-on experience with data science tools * Problem-solving aptitude * Analytical mind and great ...

Hexagon AB

Lead Data Scientist

Houston, TX · On-site

Develop predictive models for compliance risk scoring, regulatory change impact, anomaly detection ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD ...

IPT Global

Data Scientist

Houston, TX · On-site

... risk analysis, optimization * Experience with statistical/numerical software (e.g., R, Python, MATLAB), database query languages (e.g., SQL), and data science toolkits (e.g., TensorFlow, Keras ...

IPT Global

Data Scientist

Houston, TX · On-site

... risk analysis, optimization * Experience with statistical/numerical software (e.g., R, Python, MATLAB), database query languages (e.g., SQL), and data science toolkits (e.g., TensorFlow, Keras ...

IPT Global

Data Scientist

Houston, TX

... risk analysis, optimization * Experience with statistical/numerical software (e.g., R, Python, MATLAB), database query languages (e.g., SQL), and data science toolkits (e.g., TensorFlow, Keras ...

bwp

Lead / Sr Analyst Data Scientist

Houston, TX

... risk assessment. Cloud & Platform Integration * Leverage Databricks and Amazon Web Services (AWS ... Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, or a ...

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Credit Risk Data Science information

See Sugar Land, TX salary details

$33.2K

$102.1K

$177.1K

How much do credit risk data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for credit risk data science in Sugar Land, TX is $102,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,000.00 and $126,000.00 per year, depending on experience, location, and employer.

What is credit risk data science?

Credit Risk Data Science is a specialized field that uses statistical analysis, machine learning, and data modeling techniques to assess and predict the likelihood that a borrower will default on a loan or credit obligation. Professionals in this field analyze large datasets from financial transactions, credit reports, and market trends to develop models that help financial institutions make informed lending decisions. Their work helps manage risk, set appropriate interest rates, and comply with regulatory standards. By leveraging advanced analytics, credit risk data scientists play a crucial role in minimizing losses and maximizing profitability for banks and lenders.

What skills and qualifications are needed to thrive as a credit risk data scientist?

To thrive as a Credit Risk Data Scientist, you need strong analytical skills, proficiency in statistical modeling, and a solid background in finance, mathematics, or a related field, often supported by an advanced degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of credit risk modeling tools such as SAS or SQL are typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These abilities are crucial for building accurate risk models, informing strategic decisions, and ensuring regulatory compliance in financial institutions.

How does a credit risk data scientist typically collaborate with other teams within a financial institution?

Credit Risk Data Scientists often work closely with credit analysts, risk managers, and IT professionals to develop, validate, and implement models that assess borrower risk. They frequently participate in cross-functional meetings to translate complex analytical findings into actionable business insights. Collaboration with compliance and regulatory teams is also common to ensure that risk models meet current regulatory standards. Effective communication and teamwork are essential, as the role bridges technical model development and practical risk management decisions.

What job categories do people searching Credit Risk Data Science jobs in Sugar Land, TX look for?

The top searched job categories for Credit Risk Data Science jobs in Sugar Land, TX are:

What cities near Sugar Land, TX are hiring for Credit Risk Data Science jobs?

Cities near Sugar Land, TX with the most Credit Risk Data Science job openings:

Credit Risk Data Science jobs near you

Data Engineer - Data Science & Technology

Castleton Commodities International, LLC

Houston, TX • On-site

$90 - $120/hr

Other

Medical, Dental, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

At Castleton Commodities International (CCI), we are redefining how data and technology shape the future of energy trading. Our Data Science & Technology team is at the forefront of this transformation, developing systems and innovative tools that empower our front‑office teams to better understand market dynamics, forecast prices, and manage risk. Our commitment to excellence is reflected in a robust, modern, open‑source technology stack, empowering us to solve complex, high‑impact challenges at scale. From cloud‑native infrastructure to machine learning platforms, real‑time analytics, and proprietary libraries and APIs, we are passionate about using technology to drive innovation and create a competitive edge in global energy commodity trading and investing. Candidates will gain direct exposure to our commercial investment teams, offering a unique opportunity to see how cutting‑edge technology drives strategy and performance in energy markets.

Our Data Engineering team is integral to our mission, ensuring the seamless ingestion and management of data across our platforms. The Data Engineer plays an integral role: implementing new data management platforms, creating new data ingestion pipelines, and sourcing new data sets. The role will assist with all aspects of data – from data architecture design to ongoing data management – and will have significant exposure to our Commercial investing teams globally.

Responsibilities
  • Execute data architecture and data management projects for both new and existing data sources.
  • Help transition existing data sets, databases, and code to a new technology stack.
  • Manage end‑to‑end data ingestion process and publishing to investing teams.
  • Own the process of mapping, standardising, and normalising data.
  • Conduct ad‑hoc research on project topics such as vendor trends, usage best practices, big data trends, artificial intelligence, and other vendors.
  • Assess data loads for tactical errors, build out appropriate workflows, and create data quality analysis that identifies larger issues in data.
  • Actively manage vendors and capture changes in data input proactively.
  • Prioritise and resolve data issues based on business usage.
  • Assist with managing strategic initiatives around big data projects for the commercial (trading) business.
  • Partner with commercial teams to understand current data flow, data architecture, investment process, and gather functional requirements.
  • Assess gaps in current datasets and remediate.
Qualifications
  • Bachelor’s degree in Computer Science, Mathematics, Physics, Business Intelligence, or related field of study.
  • 3+ years of Data Engineering experience specializing in SQL programming, data architecture, and dimension modelling.
  • Experience in energy commodities or financial services is nice to have but not required.
  • Experience in mapping, standardising, and normalising data.
  • Experience with ETL/ELT frameworks to write pipelines that load millions/billions of records.
  • Advanced skills in writing highly optimised SQL code.
  • Experience with relational databases; Snowflake highly preferred.
  • Hands‑on experience developing data solutions in Python, Pandas, NumPy, etc.
  • Ability to communicate and interact with a wide range of data users – from very technical to non‑technical.
  • Team player with an execution focus and the ability to handle a rapidly changing set of projects and priorities while maintaining a strong professional presence.
  • Ability to work effectively in a fast‑paced, dynamic and high‑intensity environment, including an open‑floor plan, with timely responsiveness and the ability to work beyond normal business hours when required.
Employee Programs & Benefits
  • Competitive comprehensive medical, dental, retirement and life insurance benefits
  • Employee assistance & wellness programmes
  • Parental and family leave policies
  • CCI in the Community: Each office has a Charity Committee and, as a part of this program, employees are allocated 2 days annually to volunteer at selected charities.
  • Charitable contribution match programme
  • Tuition assistance & reimbursement
  • Quarterly Innovation & Collaboration Awards
  • Employee discount programme, including access to fitness facilities
  • Competitive paid time off
  • Continued learning opportunities

Visit https://www.cci.com/careers/life-at-cci/# to learn more!

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