Senior Data Scientist

Job Role:

Company:

Location:

Experience:

About the Role:

enterprise-scale datasets

Key Responsibilities:

• Develop, train, and deploy

  machine learning and deep learning models

  including RNNs, LSTMs, GANs, reinforcement learning, and other advanced algorithms.
• Analyze

  high-volume, complex datasets

  to identify patterns, trends, anomalies, and actionable insights.
• Apply

  statistical modeling techniques

  such as regression, Bayesian analysis, clustering, and predictive modeling to solve business problems.
• Collaborate with cross-functional teams to implement

  enterprise-grade data solutions

  that support strategic decision-making.
• Conduct

  model evaluation, validation, and optimization

  , including hyperparameter tuning and performance monitoring.
• Visualize and present findings effectively to

  non-technical and technical stakeholders

  using dashboards and reports.
• Stay updated with emerging trends in

  machine learning, deep learning, AI, and statistical modeling

  , and recommend innovative solutions for business challenges.
• Ensure that models and analytics practices follow

  ethical AI principles and best practices

  .

Required Qualifications:

• Bachelor’s or Master’s degree in

  Statistics, Applied Mathematics, Computer Science, or a related quantitative field

  .
• 4–8 years of experience in

  data science, predictive analytics, or applied statistics

  .
• Strong proficiency in

  Python or R

  , and experience with ML/DL libraries such as

  Scikit-Learn, TensorFlow, PyTorch, Statsmodels, or Prophet

  .
• Expertise in

  statistical modeling, regression, Bayesian methods, predictive analytics, and deep learning techniques

  .
• Hands-on experience working with

  large-scale enterprise datasets

  .
• Familiarity with

  big data platforms and cloud-based analytics workflows

  is preferred.
• Strong analytical thinking, problem-solving skills, and the ability to

  communicate complex concepts clearly

  to stakeholders.