Analyze complex credit and lending data to inform business decisions
Develop strategies to mitigate losses and support risk management and regulatory compliance
Provide actionable insights to support growth and market expansion
Collaborate with cross-functional teams and business leaders to deliver data-driven solutions
Conduct extensive data analysis using statistical and machine learning techniques
Develop predictive and prescriptive models forecasting market trends, fraud, delinquency, and customer behavior
Utilize various data sources and preprocessing techniques to ensure data quality and integrity
Design, develop, implement and maintain machine learning algorithms and AI solutions for risk assessment, fraud detection, and portfolio management
Experiment with state-of-the-art machine learning techniques to improve accuracy and efficiency
Create clear and concise data visualizations and reports for technical and non-technical stakeholders
Translate analytical results into actionable business insights and present findings to senior management
Requirements
Proven experience as an Analyst, preferably in the financial services sector, with a track record of successful project delivery and business impact
Experience in risk modeling software and tools (e.g., SAS, R, Python, Matlab) and machine learning using libraries such as NumPy, Pandas and scikit-learn
Solid understanding and practical experience with machine learning algorithms, statistical modeling, and data mining techniques
Bonus: experience with ML engineering and/or operations in a production setting
Familiarity with cloud platforms (we use GCP) for scalable data processing and analysis, and for machine learning model development and deployment
Strong knowledge of databases and SQL for data retrieval and manipulation
Experience with data visualization tools like Looker, Tableau or Power BI to create insightful reports and dashboards
Excellent problem-solving skills, analytical thinking, and the ability to thrive in a fast-paced, results-oriented environment
Effective communication and presentation skills, with the ability to communicate complex technical concepts to non-technical audiences
A Master’s or Ph.D. degree in a quantitative field such as Data Science, Statistics, Computer Science, or Mathematics is nice to have
Benefits
A flexible work environment that empowers you to do your best work
A culture that celebrates performance
The chance to make an impact in a team that’s big enough for career growth, but lean enough to make your voice heard
Career-defining opportunities
Flexible paid time off and remote work policies
Equity options, because this is your company too
Contributions to your pension plan. Your future matters
Training opportunities to grow your skills and career
Health and wellness credit so you feel your best
Time off to volunteer and give back to your community
Interest groups, employee led networks, social committees to sponsored sports teams
Computer purchase program to get your personal Macbook
Enhanced parental leave to support growing families
Medical, dental, wellness, life and disability insurance
401K plan and match
Paid parental leave top-up
Paid time off
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data analysismachine learningstatistical modelingrisk modelingdata miningpredictive modelingprescriptive modelingdata preprocessingdata visualizationSQL
Soft skills
problem-solvinganalytical thinkingcommunicationpresentation skillscollaborationstrategic thinkingadaptabilityattention to detailresults-orientedinsight generation