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Lead the design, development, deployment, and monitoring of machine learning models for financial applications. Analyze structured and unstructured data, build forecasting and predictive solutions, and ensure model scalability, interpretability, fairness, and regulatory compliance. Collaborate with technical and business stakeholders, communicate insights, develop training workflows, and mentor junior data scientists while contributing to data science strategy.
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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Ranked among the hottest tech cities in 2024 by CompTIA, Charlotte is quickly cementing its place as a major U.S. tech hub. Home to more than 90,000 tech workers, the city’s ecosystem is primed for continued growth, fueled by billions in annual funding from heavyweights like Microsoft and RevTech Labs, which has created thousands of fintech jobs and made the city a go-to for tech pros looking for their next big opportunity.
Key Facts About Charlotte Tech
- Number of Tech Workers: 90,859; 6.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lowe’s, Bank of America, TIAA, Microsoft, Honeywell
- Key Industries: Fintech, artificial intelligence, cybersecurity, cloud computing, e-commerce
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (CED)
- Notable Investors: Microsoft, Google, Falfurrias Management Partners, RevTech Labs Foundation
- Research Centers and Universities: University of North Carolina at Charlotte, Northeastern University, North Carolina Research Campus
