Data Scientist (Austin)

TWC offers flexible schedules and requires work hours that are Monday to Friday between the hours of 7:00 AM to 6:00 PM. Flex scheduling is available depending on work performance and/or demonstration of need, but the individual should have the ability to be available for most peak business hours (9:00 AM to 5:00 PM)., TWC’s Information Innovation & Insight Division is seeking a highly skilled and exceptionally motivated Data Scientist to spearhead critical data projects focused on program integrity and fraud prevention in Unemployment Insurance (UI) and Child Care and Early Learning (CCEL). We are looking for a forward-thinking individual who not only executes tasks but also works smart-proactively identifying efficient coding methods to uncover anomalies, detect fraudulent patterns, and protect agency resources. The Data Scientist will learn quickly and pursue analytical work to unlock the power of data to improve TWC’s services for Texas employers, individuals, families, and communities. If you value public service and are committed to setting the standard for high-impact performance and program security, we encourage you to apply!

The Data Scientist will work with the Unemployment Insurance, Program Integrity, and Child Care (UIPIC) team, which has eight members. The UI program is designed to help support Texans who lose their jobs through no fault of their own until they can find new employment. The team’s program integrity work is aimed at defending the UI trust fund and Texas child care system against fraud. Meanwhile, the team helps TWC’s CCEL Division strategically distribute funding and plan subsidized Child Care supports for parents and guardians who are working or looking for work.

Members of the UIPIC team operate collaboratively in an environment that encourages cross-training and peer mentorship. They frequently interact with TWC’s Fraud Deterrence and Compliance Monitoring (FDCM) Division on joint initiatives. Staff are mostly self-directed and produce high-quality research and evaluation work as well as proactively creating and applying complex statistical models to solve system problems and build better fraud detection and fund allocation systems. The Data Scientist will be a master communicator who can distill complex investigative concepts into clear, actionable insights for diverse audiences, including regulatory and law enforcement partners. You must be a natural leader and innovator with a meticulous eye for detail and a steadfast commitment to data security and confidentiality.

We will only consider applications that include all the following: (1) an attached writing sample (at least 1,000 words of business communication or technical writing) (2) an attached cover letter explaining why you are interested in the job and how you think you’d be a good fit at the Texas Workforce Commission (3) an attached resume tailored to the Data Scientist position Attached file names must be clearly labeled, containing “resume” for your resume, “cover letter” for your cover letter, and “writing sample” for your writing sample. If a file contains two items (e.g., a cover letter and writing sample), it must be labeled as such. Applications that do not follow this instruction will not be considered, even if all requested items are included.

What You Will Do: As a Data Scientist in this specialized role, you will perform complex (journey-level) data science work, from gathering and managing large datasets to designing and deploying new predictive models targeted at fraud detection and risk mitigation. Your work will generate crucial insights into program vulnerabilities, directly informing agency leadership, shaping fraud-prevention strategies, and supporting complex investigations involving sensitive law enforcement data. You will be expected to not just complete assignments but to deliver highly secure, actionable results that go well beyond baseline requirements. You will work under limited supervision, with moderate latitude for the use of initiative and independent judgment. The ideal candidate will consistently demonstrate proficiency at applying advanced quantitative analysis techniques such as: predictive analytics and forecasting; classification, clustering, association, text mining, and natural language processing; optimization models for managing product and service-oriented operations; linear programming; network optimization; immersive and flexible dashboard data visualization; qualitative/quantitative mixed methods program evaluation; and machine learning and artificial intelligence. Core tools you will work with will include:

• Python
• Git/GitHub
• SQL
• JavaScript
• HTML5
• Highcharts

You Will be Trusted To:

• Develop, deploy, and manage predictive modeling algorithms to mine large data sets specifically designed to detect anomalies, prevent fraud, and ensure overall program integrity.
• Collaborate closely with internal investigative units and external law enforcement partners to analyze sensitive data, trace fraudulent activities, and support ongoing investigations.
• Pioneer and implement cutting-edge data analysis techniques, compelling visualizations, and robust data lifecycle methods.
• Maintain strict compliance with data security protocols and handle confidential law enforcement data with the highest level of integrity and security.
• Formulate and deploy methods for mitigating and correcting issues related to data integrity, entry, and collection to prevent exploitation.
• Prepare and present concise, comprehensive technical reports that provide clear, audience-appropriate explanations of investigative findings and risk assessments.
• Serve as a subject matter expert and mentor on data integrity, anomaly extraction, and secure data compilation.
• Commit to continuous professional development, staying ahead of industry trends in cybersecurity, fraud tactics, and data protection.
• Perform other duties as assigned.

• Five years of full-time experience in experience in data science, predictive modeling, and algorithm work.
• Relevant academic credits may be applied toward experience qualifications for this position.

You Are a Great Fit With:

• Experience maintaining and deploying machine learning (ML) models in production.
• Proven ability to manage and manipulate large, complex data sets to provide advanced analysis and actionable insights.
• Exceptional skill in analyzing problems, rapidly conceptualizing solutions, and formulating effective strategies.
• Expertise in computer programming (e.g., Python, R), statistical modeling, data visualization tools, and database management.
• Computer engineering level of understanding of Python as a programming language
• A strong command of economic and demographic statistics, with experience in workforce and economic development analysis.
• Knowledge of data modeling techniques, algorithms, artificial intelligence, and data governance principles.
• A demonstrated ability to lead projects, mentor teammates, and skillfully influence others to achieve ambitious goals.
• An exceptional talent for communicating effectively with both technical and non-technical audiences.
• A strong drive for continuous learning and a proactive mindset toward improving processes and products.

Pulled from the full job description

• 401(k)
• Health insurance
• Paid time off
• Family leave, * Competitive starting salary: $7,716.66-$13,051.00 (based on qualifications)
• Defined Retirement Benefit Plan, plus optional 401(k) and 457 accounts.
• Comprehensive Medical Insurance.
• Paid time off, including vacation, sick, and family care leave.
• Additional benefits for active employees can be found at https://www.ers.texas.gov/Active-Employees/Health-Benefits.

The Texas Workforce Commission (TWC) connects people with careers across the state. The Data Scientist I position is located at 101 East 15th Street in Austin, TX. Work will be full-time on-site. We’re a Family Friendly Certified Workplace with a great work-life balance, competitive salaries, extensive opportunities for training and professional development, and fantastic benefits. This position is in the Info Innovation & Insight division.