Data Science Manager, Risk

Klarna Bank AB

What you will do Perform independent end-to-end validation of fraud detection ML models, including conceptual soundness, data integrity, feature engineering, model development, deployment design, and monitoring frameworks. Develop challenger models. Review and challenge first-line fraud model methodologies, assumptions, and implementation choices (e.g., scikit-learn, LightGBM, graph models, anonaly detection techniques, GenAI components). Build and deploy agentic AI tools to support model validation workflows — automating review of model documentation and code, surfacing risks and inconsistencies. Assess model performance using appropriate fraud metrics (e.g., precision/recall, ROC-AUC, PR-AUC, cost-sensitive metrics, fraud rate capture, business impact trade-offs). Evaluate model stability, drift detection, retraining strategies, and production monitoring practices. Independently replicate model results where necessary and conduct challenger analyses to assess model robustness and limitations. Review large-scale transaction datasets and feature pipelines (e.g., >100M transactions, hundreds of features) to assess data representativeness, leakage risks, and bias. Evaluate model governance documentation, explainability approaches, and transparency — including regulatory compliance related to model risk, fairness, and data privacy. Validate new technologies applied in fraud detection, such as Graph Networks, Behavioral Biometrics, Anomaly Detection, and GenAI-based systems. Assess controls around CI/CD pipelines, deployment processes (e.g., Docker, Jenkins), and cloud environments (e.g., AWS SageMaker, S3, Athena, Lambda). Develop and maintain validation frameworks, testing standards, and model performance monitoring tools (e.g., SQL, PySpark, Python-based validation libraries). Collaborate closely with first-line fraud data scientists, ML engineers, product, and business stakeholders to ensure transparent communication of model risks and validation findings. Provide actionable recommendations and formally document validation outcomes in line with internal model governance standards and external regulatory expectations. Stay up to date with evolving fraud typologies, emerging ML/AI techniques, and regulatory developments in model risk management. Who you are Advanced degree (Master’s or PhD) in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Physics, or Engineering. 3+ years of hands-on experience in fraud-related modeling (e.g., transaction fraud, account takeover, identity fraud, payments fraud etc). Strong expertise in machine learning methods used in fraud detection, including tree-based models (e.g., LightGBM), anomaly detection, graph/network models, and advanced ML techniques. Deep understanding of the end-to-end ML lifecycle — from conceptual design and feature engineering to production deployment and monitoring — with the ability to critically challenge each stage. Strong programming skills in Python and SQL; experience with PySpark/Spark and large-scale data processing. Experience building agentic AI workflows. Familiarity with cloud-based ML platforms (e.g., AWS SageMaker, Lambda, S3, Athena) and production deployment workflows. Strong knowledge of model validation principles, model risk governance frameworks, and regulatory expectations. Experience assessing model bias, fairness, explainability, and privacy risks. Excellent analytical thinking and structured problem-solving skills, with the ability to assess complex models and clearly articulate risks and limitations. Strong communication skills, capable of translating technical findings into clear, actionable insights for senior stakeholders and non-technical audiences. Ability to work independently while constructively challenging first-line teams in a collaborative manner. Awesome to have Experience in BNPL, credit cards, payments, or other transaction-heavy financial products. Experience validating models in highly regulated environments. Experience mentoring junior validators or leading validation reviews. Exposure to inference of rejected transactions and understanding of fraud/credit overlap. Familiarity with AI governance frameworks and emerging AI regulatory requirements.

Sofi

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role The Data Science team is seeking a Senior Manager who will help support growth in our SIPS businesses by improving SoFi’s ability to execute with data.  This is an exciting role for someone to leverage their Analytical, Engineering, and Management skills to lead a team of Data Scientists with high visibility and impact. You will serve as a data leader, balancing urgent requests and delivering high quality projects to key stakeholders, through a clear and repeatable data informed approach.  You will create a culture of strong technical ownership, deliver impact with prioritization, support the growth of individual contributors, and hold the team accountable with high standards. You are expected to work cross-functionally, including: engineering, product managers, lifecycle marketing, data science, design, operations, finance, risk, legal, compliance, and executive teams to set business objectives, define product strategy, prioritize features, and execute on them.   What you’ll do: * Manage a team of Data Scientists supporting SoFi’s Checking and Savings, Invest, Credit Card, Protect, and Lantern businesses * Collaborate with senior leaders and other stakeholders to identify and prioritize Data Science initiatives * Set high standards for quality and on-time delivery. * Recruit, grow, and retain top talent * Ensure that the team is operating in an agile and efficient manner * Stay up-to-date on the latest AI/ML technologies * Identify high impact business opportunities to help members achieve their financial goals * Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation. * Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and non-technical stakeholders * Collaborate with cross-functional teams and business leaders to understand needs and offer data-driven solutions   What you’ll need: * Bachelor’s Degree in a technical field * 7+ years of Data Science or Software Engineering experience * 3+ years management experience * Experience leveraging data-driven analysis to influence key decisions, preferably in a Tech or Finance company * Experience with using Airflow and DBT to build Data Pipelines in Snowflake * Strong programming skills in SQL and Python * Experience with building data visualizations with Tableau, Looker or other BI tools * Knowledge of varied ML algorithms, applicability to different business problems, and experience in deploying ML models at scale in production with monitoring metrics. * Ability to work in a dynamic, cross-functional environment, with a strong attention to detail; * Effective communication and presentation skills and ability to explain complex analyses in simple terms to business leaders; * Strong relationship building and collaborative skills; * Exceptional problem-solving  Compensation and Benefits The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.    To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page! SOFI PROVIDES EQUAL EMPLOYMENT OPPORTUNITIES (EEO) TO ALL EMPLOYEES AND APPLICANTS FOR EMPLOYMENT WITHOUT REGARD TO RACE, COLOR, RELIGION (INCLUDING RELIGIOUS DRESS AND GROOMING PRACTICES), SEX (INCLUDING PREGNANCY, CHILDBIRTH AND RELATED MEDICAL CONDITIONS, BREASTFEEDING, AND CONDITIONS RELATED TO BREASTFEEDING), GENDER, GENDER IDENTITY, GENDER EXPRESSION, NATIONAL ORIGIN, ANCESTRY, AGE (40 OR OVER), PHYSICAL OR MEDICAL DISABILITY, MEDICAL CONDITION, MARITAL STATUS, REGISTERED DOMESTIC PARTNER STATUS, SEXUAL ORIENTATION, GENETIC INFORMATION, MILITARY AND/OR VETERAN STATUS, OR ANY OTHER BASIS PROHIBITED BY APPLICABLE STATE OR FEDERAL LAW. THE COMPANY HIRES THE BEST QUALIFIED CANDIDATE FOR THE JOB, WITHOUT REGARD TO PROTECTED CHARACTERISTICS. PURSUANT TO THE SAN FRANCISCO FAIR CHANCE ORDINANCE, WE WILL CONSIDER FOR EMPLOYMENT QUALIFIED APPLICANTS WITH ARREST AND CONVICTION RECORDS. NEW YORK APPLICANTS: NOTICE OF EMPLOYEE RIGHTS SOFI IS COMMITTED TO AN INCLUSIVE CULTURE. AS PART OF THIS COMMITMENT, SOFI OFFERS REASONABLE ACCOMMODATIONS TO CANDIDATES WITH PHYSICAL OR MENTAL DISABILITIES. IF YOU NEED ACCOMMODATIONS TO PARTICIPATE IN THE JOB APPLICATION OR INTERVIEW PROCESS, PLEASE LET YOUR RECRUITER KNOW OR EMAIL ACCOMMODATIONS@SOFI.COM. DUE TO INSURANCE COVERAGE ISSUES, WE ARE UNABLE TO ACCOMMODATE REMOTE WORK FROM HAWAII OR ALASKA AT THIS TIME. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

Databricks

RDQ225R487 JOB DESCRIPTION Databricks is looking for a Senior Manager, Infrastructure Data Science to shape the future of Databricks infrastructure through data science. You will tackle some of the most complex challenges related to capacity planning, performance optimization, reliability engineering, infrastructure efficiency, and customer experience.  You will lead a team of data scientists and work directly in partnership with engineering leaders to empower them with data-driven insights and solutions.  At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 7000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. The impact you will have: * Thought leadership and strategic guidance on infrastructure planning, balancing current needs with future growth projections to ensure scalability and cost-effectiveness. * Promote a data-driven approach to infrastructure decisions, influencing stakeholders across engineering, and support to leverage data science insights for high-impact, aligned strategies. * Implement data-driven solutions to identify, predict, and mitigate infrastructure risks and failures, reducing downtime and improving system reliability and performance, directly impacting end-user satisfaction and operational continuity. * Spearhead analyses to improve resource utilization efficiency, identifying and eliminating inefficiencies across infrastructure usage, resulting in cost savings and optimized performance. * Establish data frameworks that empower support teams to troubleshoot and resolve product issues faster, decreasing response times and enhancing customer experience and support quality. * Mentor and manage a team of data scientists, instilling best practices in data science, engineering, and fostering a collaborative environment focused on innovative, scalable infrastructure solutions.   What we look for: * 10+ years of infrastructure data science, machine learning, advanced analytics experience in high velocity, high-growth companies * 5+ years of management experience hiring and developing teams * Experience developing data science, analytics, and machine learning and AI products and capabilities in a cloud environment * Knowledge of statistics and rigorous analytical techniques * Experience with data visualization tools, knowledge of data engineering, data modeling, and big data technologies * Leadership skills and experience to lead across functional and organizational lines * Strong communication skills to explain and evangelize analytics and data science to executives and the senior management team * Bias to action and passion for delivering high-quality data solutions * A passion for problem-solving and comfort with ambiguity * MS or Ph.D. in quantitative fields (Statistics, Math, CS or Engineering)   Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.   Zone 1 Pay Range $228,600—$314,250 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.