Role Overview:

We are looking for a Senior Data Scientist who can independently lead machine learning initiatives from problem identification through implementation and ongoing performance improvement.

The role requires a combination of strong analytical expertise, practical business understanding, and the ability to develop scalable solutions that can be integrated into business operations.

The candidate will work closely with business stakeholders and technology teams to identify opportunities for applying data science, improve existing models and processes, and ensure that developed solutions deliver measurable business value.

Key Responsibilities:

- Work with business stakeholders to understand key challenges and identify opportunities where data science and machine learning can drive better outcomes.

- Lead the development, validation, and improvement of machine learning models for prediction, forecasting, risk assessment, and other business applications.

- Manage the end-to-end delivery of data science solutions, from data analysis and model development to deployment and performance monitoring.

- Develop automated and reusable processes to improve the efficiency, consistency, and scalability of analytical solutions.

- Identify opportunities to improve existing models, business processes, and decision-making through advanced analytics.

- Collaborate with data engineering, technology, and business teams to integrate models into operational workflows.

- Establish appropriate processes to track model performance, identify potential issues, and drive continuous improvement.

- Ensure solutions meet business requirements and adhere to quality, governance, and documentation standards.

- Provide technical guidance and support to junior team members.

- Communicate analytical findings, recommendations, and business implications to stakeholders.

Required Skills & Experience:

- 5 - 7 years of experience in data science, machine learning, or advanced analytics.

- Strong proficiency in Python, SQL, and statistical analysis.

- Demonstrated experience in developing and deploying machine learning models in business or enterprise environments.

- Experience managing end-to-end machine learning projects and improving model performance.

- Understanding of automated workflows, model monitoring, and production implementation.

- Strong problem-solving, stakeholder management, and communication skills.

- Ability to independently manage deliverables and collaborate across business and technology functions.

Preferred Qualifications:

- Experience in banking, financial services, lending, credit risk, fraud detection, or risk analytics.

- Exposure to cloud-based machine learning platforms and enterprise data environments.

- Experience mentoring junior team members or leading small project teams.

- Bachelor's or master's degree in a relevant technical or quantitative discipline.