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.
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