Data Analyst at GDIT delivering insights to help clients improve data utility. Collaborating with teams for report development and data visualization in Bossier City, LA.
About the role
- Risk Data Analyst at Teya, focusing on fraud detection and financial crime monitoring. Collaborating with cross-functional teams to enhance analytical intelligence and drive data-informed decisions.
Responsibilities
- Develop and refine the intelligence used to detect financial crime, balancing efficacy with operational efficiency to reduce false positives, investigation time, and customer friction
- Deliver actionable insights that directly improve detection rates, uncover new risk patterns, and inform prevention strategies
- Act as a bridge between data and the business, collaborating closely with Operations, Compliance, Engineering, and Product teams to shape and prioritise analytical initiatives
- Identify opportunities to improve and automate monitoring, escalate emerging threats, and continuously evolve our understanding of risk
- Build and maintain clear and impactful dashboards, reports, and documentation to monitor key metrics, surface relevant trends, and drive data-informed decisions
- Partner with data engineering to design and maintain scalable, reliable data models and ETLs that underpin both operational and strategic use cases
- Help define and analyse fraud and AML KPIs, helping the business plan and course-correct with confidence
- Promote a culture of data-driven decision-making across the organisation
Requirements
- A minimum of two years of professional experience as a data analyst, working in financial crime and/or transaction monitoring
- Direct experience with problems such as AML scenario tuning, fraud rule optimisation, or the design of detection intelligence is strongly preferred.
- Experience in producing insights that led to measurable improvements, ideally in relevant domains such as fraud, AML detection, or operations
- Advanced proficiency in SQL and experience working with large, complex, and sometimes messy datasets
- Experience designing, building, and maintaining ETL pipelines or data models, ideally using tools like dbt
- Proficient in Tableau or equivalent BI tool
- Proficiency in Python for data analysis, including data manipulation, visualisation, and basic modelling
- Strong data storytelling and communication skills: you can translate complex data into clear, actionable recommendations for both technical and non-technical stakeholders
- Experience working collaboratively with cross-functional partners, including Operations, Compliance, Engineering and Product
- Self-starter who thrives in a fast-paced, high-ambiguity environment and takes ownership of their work from start to finish
Benefits
- Health Insurance
- Meal Allowance
- 25 days of Annual leave (+ Bank holidays)
- Public Transportation Card
- Frequent team events & activities in the office and outside
- Office snacks every day
- Friendly, comfortable and informal office environment
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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