Role Overview:

We are looking for a Data Scientist with experience in developing machine learning models and translating data into actionable business insights.

The role involves working on business problems across the model development lifecycle, from understanding requirements and analyzing data to developing, deploying, and monitoring ML solutions.

The ideal candidate should have strong analytical and problem-solving skills, good programming knowledge, and the ability to collaborate with business and technology teams to deliver practical, scalable solutions.

Key Responsibilities:

- Understand business requirements and translate them into analytical and machine learning solutions.

- Develop, test, and improve machine learning models for business applications such as prediction, forecasting, classification, and risk assessment.

- Analyze large datasets to identify patterns, trends, and opportunities for business improvement.

- Build automated workflows to support data processing, model execution, and reporting.

- Support the deployment of machine learning models into business applications and operational processes.

- Monitor model performance and identify opportunities to improve accuracy, reliability, and efficiency.

- Work closely with data engineering, technology, and business teams to deliver end-to-end solutions.

- Ensure that analytical solutions are reliable, well-documented, and aligned with business requirements.

- Stay updated on emerging data science techniques and identify opportunities to apply them to business challenges.

Required Skills & Experience:

- 3 - 5 years of experience in data science, machine learning, or advanced analytics.

- Strong proficiency in Python and SQL.

- Hands-on experience in developing and evaluating machine learning models.

- Understanding of statistical techniques, data analysis, and feature engineering.

- Experience in automating analytical workflows and supporting model deployment.

- Ability to communicate analytical findings and work effectively with cross-functional teams.

Preferred Qualifications:

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

- Exposure to cloud-based analytics and machine learning platforms.

- Bachelor's or master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field.