The Role
Build, tune, deploy, and validate machine learning models for fraud detection, risk scoring, and customer analytics in the BFSI and credit card domain. The role involves performance and stability testing, documentation, troubleshooting data and model issues, communicating findings to varied stakeholders, managing analytical projects independently, and staying current with emerging AI and ML techniques.
Summary Generated by Built In
About the Role
We are looking for a driven and detail-oriented Data Scientist to join our team. The ideal candidate will bring strong hands-on experience in Machine Learning and model validation. This role requires someone who can independently drive analytical projects, communicate findings clearly to stakeholders, and continuously learn and adapt in a fast-paced environment.
Key Responsibilities
- Design, build, and validate machine learning models to solve business problems within the BFSI / credit card domain (e.g., fraud detection, risk scoring, customer behavior analytics)
- Perform rigorous model validation, including performance testing, stability checks, and documentation to meet internal and regulatory standards
- Translate business problems into structured data science approaches, and communicate technical findings to both technical and non-technical stakeholders
- Apply strong problem-solving skills to troubleshoot data issues, model performance gaps, and business edge cases
- Work independently with minimal supervision, managing multiple priorities and deadlines with strong organizational discipline
- Stay current with evolving ML/AI techniques and proactively bring new ideas and approaches to the team
Required Qualifications
- Proven experience in Machine Learning - building, tuning, and deploying models
- Experience with model validation practices (performance metrics, stability/drift checks, documentation)
- Strong communication skills, able to explain technical concepts to varied audiences
- Strong problem-solving ability with a structured, analytical approach
- Strong organizational skills and ability to manage work independently
- A quick learner with genuine enthusiasm for picking up new tools, techniques, and domain knowledge
Preferred (Good to Have)
- Experience with AI techniques/tools beyond traditional ML (e.g., LLMs, generative AI applications)
- Background or working understanding of the BFSI / Credit Card business
- Familiarity with cloud-based ML platforms (e.g., AWS SageMaker) and explainability techniques (e.g., SHAP)
- Exposure to regulatory/compliance considerations in financial model development
Skills Required
- Proven experience building, tuning, and deploying machine learning models
- Experience with model validation, including performance metrics, stability or drift checks, and documentation
- Strong communication skills for explaining technical concepts to technical and non-technical audiences
- Strong problem-solving ability with a structured, analytical approach
- Strong organizational skills and ability to work independently
- Ability to learn new tools, techniques, and domain knowledge quickly
- Experience with AI techniques or tools beyond traditional machine learning, such as LLMs or generative AI
- Background or working knowledge of BFSI or credit card businesses
- Familiarity with cloud-based ML platforms such as AWS SageMaker and explainability techniques such as SHAP
- Exposure to regulatory or compliance considerations in financial model development
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The Company
What We Do
Proclink is a digital and AI transformation company that helps regulated and operationally intensive enterprises modernize systems, workflows, and decision environments. It combines strategy and consulting, data engineering, artificial intelligence, analytics, implementation and integration, managed services, and technology services. The company serves manufacturing, financial services, life sciences, and other regulated industries, delivering connected enterprise intelligence and measurable operational performance for clients.
