Senior Data Scientist

Senior Data Scientist / Lead

Key Responsibilities:

• Design, develop, and implement

  machine learning models

  and

  statistical algorithms

  to address complex business challenges in banking and fintech.
• Analyze large and diverse datasets to derive

  actionable insights

  and enable

  data-driven decision-making

  across functions.

• Lead, mentor, and guide

  a team of junior data scientists and analysts, fostering a collaborative and high-performance culture.
• Collaborate closely with

  product managers, engineers, and business stakeholders

  to translate business needs into robust data science solutions.
• Build and maintain

  scalable data pipelines

  , model training workflows, and

  automated deployment

  systems.
• Stay abreast of the latest trends and advancements in AI/ML, and identify opportunities to

  enhance model accuracy, efficiency, and scalability

  .
• Ensure model governance, interpretability, and compliance with data privacy and regulatory standards.
  

Required Qualifications:

• 8 to 15 years

  of proven experience in

  data science, machine learning

  , or advanced analytics roles.
• Strong domain knowledge and practical experience in

  banking, financial services, or fintech

  is highly preferred.
• Proficient in

  Python

  (pandas, NumPy, scikit-learn, etc.) and/or

  R

  for statistical analysis and machine learning.
• Deep understanding of

  predictive modeling

  ,

  classification

  ,

  clustering

  ,

  regression

  ,

  time-series forecasting

  , and

  optimization techniques

  .
• Hands-on experience with

  SQL

  and working with

  large-scale datasets

  .
• Familiarity with

  cloud platforms

  such as

  AWS, GCP, or Azure

  is a strong advantage.
• Excellent

  analytical thinking

  ,

  problem-solving

  , and

  communication

  skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Masters or PhD in Computer Science, Statistics, Mathematics, Data Science, or a related field.
  
• Experience with tools like TensorFlow, PyTorch, Spark, or MLflow.
  
• Exposure to model monitoring, drift detection, and MLOps best practices.