Leads the design, development, deployment, and monitoring of machine learning models for financial applications. Analyzes large structured and unstructured datasets, develops scalable training workflows, and ensures model interpretability, fairness, and regulatory compliance. Collaborates with product, engineering, and business teams to deliver actionable solutions, communicates findings to varied audiences, and mentors junior data scientists. Uses generative AI, MLOps, cloud platforms, and visualization tools to drive business value.
We are looking for an experienced and driven Senior Data Scientist to join our team and lead the development of AI-powered solutions. As a Senior Data Scientist, you will work closely with teams to design, implement, and deploy data-driven solutions that drive business value. You will help shape our data science strategy, mentor junior team members, and ensure the robustness and scalability of our models in production environments.
What you'll need to bring to the role & Experian
- A Bachelor's/Master's/Ph.D. degree in computer science, Statistics, Mathematics, Data Science, or a related field.
- 5+ years of experience in data science or machine learning, with a strong track record of delivering impactful solutions.
- Proficiency in Python and ML frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, or similar.
- Experience with statistical modeling, time series forecasting, supervised and unsupervised learning, and optimization techniques.
- Experience with generative AI principles.
- Intermediate to fluent English proficiency – technical concepts clearly in English is essential.
- Experience working with financial datasets (e.g., credit scoring, fraud detection, risk modeling, pricing, or forecasting).
- Proficiency in SQL and experience with relational and non-relational databases (e.g., PostgreSQL, CosmosDB, MongoDB).
- Experience deploying models into production using Databricks and cloud platforms (AWS, GCP, or Azure).
- Familiarity with MLOps practices, CI/CD pipelines, and model monitoring tools.
- Experience with data visualization tools (e.g., Plotly, Tableau) to communicate insights effectively.
Work that matters - What you'll be doing
- Lead the design, development, and deployment of machine learning models to solve high-impact financial problems.
- Collaborate with product managers, engineers, and business stakeholders to define data science use cases and translate them into actionable solutions.
- Analyse large-scale structured and unstructured datasets to extract insights and build predictive models.
- Develop and maintain robust model training workflows.
- Ensure model interpretability, fairness, and compliance with regulatory standards.
- Mentor junior data scientists and contribute to the growth of the data science team.
• • Communicate findings and recommendations clearly to both technical and non-technical audiences.
Similar Jobs
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.
Top Skills:
Active LearningAsrData PipelinesEnsemble LabelingGdprLlmsMachine LearningNlpPseudo-LabelingPythonTts
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Senior Data Scientist applying advanced analytics and AI/ML to optimize healthcare contact center sales, Medicare conversion, DTC engagement, intelligent routing, agent performance, and conversation workflows. The role analyzes contact center and customer journey data, translates business needs into technical requirements, validates solutions through UAT and release readiness, and partners with stakeholders across sales, operations, product, engineering, QA, and architecture.
Top Skills:
Artificial IntelligenceCloud AnalyticsDatabricksMachine LearningSQLTelephony And Routing Systems
.png){kind=logo}
AdTech • Cloud • Digital Media • Information Technology • News + Entertainment • App development
Lead data strategy for large 2D and 3D media datasets used in production machine learning. Coordinate with ML, annotation engineering, and technical program management teams; translate project goals into actionable data specifications; oversee dataset curation, filtering, and processing; and ensure data integrity, representativeness, and quality through analysis and inspection.
Top Skills:
3D DataComputer VisionConfluenceExperiment Tracking FrameworkFiftyoneGitGit ServerJIRAMachine LearningPythonSlackUnix Shell
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
