Responsible for leveraging advanced analytics, machine learning, and customer intelligence to drive sustainable customer and revenue growth across the M Pesa business.
Responsibilities
Co-creating and deploying advanced machine learning and artificial intelligence solutions that drive revenue growth, cost optimization, customer retention, and enhanced customer experience.
Developing big data monetization propositions and managing their end-to-end execution to unlock commercial value from customer data and behavioral insights.
Delivering actionable customer insights, predictive analytics, and segmentation strategies that support M-Pesa objectives, commercial targets, and business decision-making.
Designing and optimizing personalized customer lifecycle campaigns, including acquisition, activation, retention, reactivation, cross-sell, and upsell initiatives.
Driving customer value enhancement through time to action, causal inference, difference in difference propensity modelling, churn prediction and customer journey optimization initiatives.
Requirements
Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Actuarial Science, or a related quantitative discipline.
Master's Degree in Data Science, Analytics, Artificial Intelligence, Business Analytics, or MBA (preferred).
Design and develop AI-powered automation solutions for enterprise workflows and business processes, build and evaluate proof‑of‑concepts, and collaborate with engineering teams to transition research concepts into production-ready solutions.
Compensation
The U.S. base salary range for this position is $112,500.00 - $187,500 annually. Regular, fulltime non-sales positions may be eligible to participate in TransUnion’s annual bonus plan. Certain positions may be also eligible for long-term incentives and other payments based on applicable company guidance and plan documents.
Responsibilities
Design and develop AI-powered automation solutions for enterprise workflows and business processes.
Design knowledge management, semantic search, and retrieval systems.
Drive innovation in areas such as neuro-symbolic AI, reasoning systems, knowledge-enhanced machine learning, agentic AI, causal AI, explainable AI, human-AI collaboration.
Design, build, and evaluate proof-of-concepts that demonstrate the value of emerging AI technologies within TransUnion's products and services.
Create repeatable frameworks for assessing AI capabilities, limitations, risks, and business impact.
Lead a high‑performing engineering team focused on healthcare escalations, automation, and EHR integrations.
Responsibilities
Lead a high‑performing engineering team focused on healthcare escalations, automation, and EHR integrations.
Own critical escalation management: drive root cause analysis, implement sustainable fixes, and reduce repeat incidents for high‑severity healthcare issues.
Define and execute the roadmap for automation, observability, and AI/ML adoption to improve reliability, predictive monitoring, and self‑healing capabilities.
Partner directly with healthcare customers on EHR modernization, interoperability, and clinical trial data integrations; ensure alignment with HIPAA, FHIR, HL7, and related standards.
Establish a culture of continuous improvement through playbooks, metrics dashboards, and knowledge sharing.
Requirements
Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field
Nice to have: 10+ years of relevant technical experience
Nice to have: 4–5 years in healthcare IT and integrations
Nice to have: leadership of cloud‑native solutions
The Principal Data Scientist is a seasoned professional role that applies in-depth disciplinary knowledge to develop new techniques and improve processes within the function, coordinating with cross‑functional teams and influencing business decisions.
Responsibilities
Hands on design and orchestration of AI solutions to evaluate, recommend, and support the implementation of business strategies
Mentor a small team (2-5 people) and guide them in fundamental system design principles w.r.t. Gen AI/Agentic AI pipelines/workflows
Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies
Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / algorithms and data visualization techniques
Incumbents in this role may often be referred to as Data Scientists
A seasoned professional role focused on designing and orchestrating AI solutions, mentoring teams in Gen AI/Agentic AI pipelines, and working with complex datasets to support business strategies within the financial industry.
Responsibilities
Hands on design and orchestration of AI solutions to evaluate, recommend, and support the implementation of business strategies
Mentor a small team (2-5 people) and guide them in fundamental system design principles w.r.t. Gen AI/Agentic AI pipelines/workflows
Work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies
Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which include utilizing statistical models / algorithms and data visualization techniques
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.
Requirements
Bachelors/University degree or equivalent experience
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