Contribute to the ML Roadmap : Identify and prioritize AI/ML opportunities across key areas such as credit risk, fraud detection, customer acquisition, and churn prevention
Prototype & Scale : Design, build, and deploy ML models that brings value to HALA, starting with rapid prototyping and scaling up based on impact
Data Strategy : Collaborate with engineering, product, and business teams to improve data collection practices and ensure we’re capturing the right signals for modeling
As a Data Scientist at CodePath, you will work across the full analytics and modeling lifecycle, supporting data pipelines, conducting exploratory analysis, building statistical and machine learning models, and developing the insights that guide organizational strategy. You will collaborate closely with data engineering and cross-functional partners to ensure our data systems, analyses, and models enable student success, operational efficiency, and accurate impact measurement. This role is ideal for someone who enjoys solving problems in a fast-paced environment, applies clear analytical thinking, and wants to grow by supporting high-impact projects that advance CodePath’s data and AI work.
CodePath is reprogramming higher education to create the first generation of AI-native engineers, CTOs, and founders.
This role is pivotal in building and scaling a team responsible for pricing, credit limit modelling, and production credit model deployment. You’ll work closely with our Consumer Credit, Product, and Engineering teams to shape how we assess and price risk, design credit products, and measure outcomes across the credit lifecycle. You’ll build the analytics and modelling foundations that inform underwriting, customer acquisition, retention, and portfolio performance at scale.
Moniepoint is a global fintech building modern financial services for millions of people and businesses across high-growth markets.
Partner with stakeholders to translate business challenges into data science problems.
Own the end-to-end lifecycle of data science models, from data exploration to deployment.
Develop scalable and efficient models, balancing algorithmic complexity with business needs.
Ocrolus helps lenders automate workflows with confidence, streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions.
Evaluate traditional, alternative, transactional, and raw datasets for use in underwriting, portfolio management, collections, and fraud.
Lead quantitative due diligence for M&A targets and data partnerships, assessing data quality, depth, coverage, stability, and scalability.
Design and implement validation frameworks to measure predictive lift, segmentation value, and incremental performance versus incumbent data.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), they have a team of 22,500 people across 32 countries and corporate headquarters are in Dublin, Ireland.
The Senior Data Scientist will solve meaningful problems, collaborate across teams, and turn complex data into clear, actionable insights. They will work at the intersection of data, product, and engineering to uncover insights, guide strategic decisions, and develop models that enhance user experience and business outcomes. They will design and deliver end-to-end data science solutions that support product innovation and business strategy.
Moniepoint Inc. is Africa’s all-in-one financial ecosystem, helping 10 million businesses and individuals access seamless payments, banking, credit, and business management tools since 2019.
Partner closely with AI Decisioning customers and internal engineering teams.
Diagnose model behavior, tune ML levers, and analyze incrementality.
Explain insights to marketers and executives.
Hightouch is the modern AI platform for marketing and growth teams, partnering with industry leaders like Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others.
Work on impactful AI and machine learning projects and contribute to solutions. Help build and support machine learning models and AI systems that power Experian's products and services. Participate in research and experimentation with new AI techniques and tools and machine learning models focusing on real-world applications.
Experian is a global data and technology company, powering opportunities for people and businesses around the world.
Build, lead, and mentor a machine learning engineering team, taking a hands-on approach while assuming increasing management responsibilities as the team grows
Design, develop, and deploy machine learning models to strengthen risk management and fraud detection capabilities
Own technical direction within the risk and fraud domain, helping define strategy, architecture, and best practices
Jobgether is a company that uses an AI-powered matching process to ensure applications are reviewed quickly, objectively, and fairly against the role's core requirements. They identify the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
Lead the vision and delivery of data driven models to optimize the delivery experience.
Collaborate with business, product, and engineering partners to deliver data science solutions.
Build data driven, robust and replicable data science models.
Gopuff is a high-growth startup revolutionizing hyper-local instant e-commerce by warehousing and delivering tens of thousands of products quickly. They're assembling a team of motivated people to drive forward their vision and bring a new age of convenience to an unpredictable world.
Building, maintaining and enhancing credit risk models for lending portfolios.
Extract, clean and manipulate large data sets using SQL and Python; build pipelines and analytics to perform model and portfolio monitoring.
Perform exploratory data analysis (EDA) to identify portfolio trends, drivers of loss performance and provide insight into model deviations.
Achieve is a digital personal finance company that provides personalized financial solutions. They leverage data and analytics to offer personal loans, home equity loans, debt consolidation, and financial tools. They have over 3,000 employees and a strong people-first culture.
Own the design and development of scalable, reliable data assets that drive real-time fraud detection, dispute operations, and regulatory reporting.
Lead the creation of high-quality labeled datasets that power supervised machine learning, rules-based fraud detection and predictive chargeback modeling
Build and maintain real-time dashboards and reporting mechanisms that provide leadership, operations and product teams with visibility into critical KPIs across Risk, Fraud and Disputes
Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office.
The Senior Data Scientist will collaborate with cross-functional teams to design, develop, and deploy machine learning models. The role involves research, experimentation, and innovation to advance AI capabilities in financial and operational analytics. The position will also mentor junior team members and contribute to technical strategy, ensuring scalable, reliable, and explainable AI solutions.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
Build and deploy production machine learning models and pipelines end-to-end.
Lead technical innovation across the data science organization.
Develop financial models using alternative data sources.
Happy Money is a consumer finance company that empowers people to achieve their goals through simple, transparent loans funded by trusted financial institutions.
Design and deploy production-ready ML solutions, leveraging cutting-edge platforms.
Conduct causal analysis to guide high-stakes business strategy.
Integrate models into production systems and monitor their performance using advanced observability tools.
CSC Generation is the AI-native holding company re-engineering omni-channel retail by acquiring iconic brands and transforming them with their operating platform.
Design and evaluate strategies to reduce fraud and abuse across promotions, referrals, refunds, and payment flows.
Develop and improve machine learning models, rules-based systems, and heuristics to detect high-risk behavior while minimizing false positives.
Analyze experimental and observational data using A/B testing and causal inference to measure the effectiveness of interventions in payments and fraud prevention.
Lime is the largest global shared micromobility business. Their electric bikes and scooters have powered more than one billion rides in cities around the world.
Be the day‑to‑day analytics partner for clients on credit strategy, risk optimization, and portfolio performance.
Translate client goals into clear analytical questions, project plans, and structured workflows.
Use Python and SQL to explore data, validate hypotheses, and support analytical workflows developed by Data Science teams.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), they have a team of 22,500 people across 32 countries.
Leverage advanced data analytics to derive insights and optimise credit strategies across products and geographies.
Partner with Engineering to design and build scalable risk models and credit risk capabilities.
Collaborate closely with Product, Legal, and Compliance teams to interpret evolving regulatory and market requirements across jurisdictions, and translate them into credit policy, underwriting, and product design recommendations.
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. They are a fast-growing FinTech company committed to redefining responsible consumer lending.