Data Scientist: AI & ML for Business Transformation

Tata Consultancy Services; Minneapolis (MN); On-site; USD 110,000 - 120,000; Full time

Benefits offered by this job

Medical Coverage

Parental Leaves

401K Plan

Certification & Training Reimbursement

Job summary

Tata Consultancy Services is seeking a Data Scientist to drive business transformation through Advanced Analytics, AI, and ML. Build predictive models, identify optimization opportunities, and translate business challenges into data-driven solutions.

Apply rigorous analysis to deliver measurable outcomes across the enterprise. The role requires collaboration with business, operations, and technology teams to define analytical requirements and develop reusable assets that improve operational

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, CS, Engineering, Economics, or related field.
• 3+ years of experience in Data Science, ML, AI, or Advanced Analytics.
• Strong foundation in statistics and predictive modeling.
• Experience with large-scale datasets and analytical languages.

Responsibilities

• Analyze structured and unstructured datasets to identify trends and insights.
• Develop and deploy predictive, classification, clustering, and optimization models.
• Apply ML, statistics, and AI techniques to solve business problems.
• Identify patterns in complex datasets and support experimentation and model validation.
• Present analytical findings to stakeholders and translate results into actions.

Skills

Python

SQL

R

Statistics

Machine Learning

Data Visualization

Communication

Education

Bachelor's degree in a quantitative field

Tools

Scikit-learn

TensorFlow

PyTorch

XGBoost

Job description

Tata Consultancy Services is seeking a Data Scientist to drive business transformation through Advanced Analytics, AI, and ML. Build predictive models, identify optimization opportunities, and translate business challenges into data-driven solutions.

Apply rigorous analysis to deliver measurable outcomes across the enterprise. The role requires collaboration with business, operations, and technology teams to define analytical requirements and develop reusable assets that improve operational