About the Role:

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 45 years of hands-on industry experience.

The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning techniques to solve complex business problems.

Key Responsibilities:

- Analyze large datasets to extract meaningful insights and patterns to support business decisions.

- Develop, implement, and optimize machine learning and statistical models for predictive and prescriptive analytics.

- Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.

- Design and build data pipelines and perform data wrangling using Python, R, or SQL.

- Communicate analytical findings through clear data visualizations and storytelling techniques.

- Evaluate model performance and improve accuracy and efficiency.

- Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML models in production.

- Ensure data quality, governance, and compliance with organizational standards.

Required Skills and Qualifications:

- Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.

- PhD in Data Science or related fields is preferred.

- 45 years of relevant experience in Data Science or Machine Learning projects.

- Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.

- Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.

- Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.

- Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.

- Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.

- Excellent analytical, problem-solving, and communication skills.

Good to Have:

- Experience with Deep Learning, NLP, or Time Series Analysis.

- Exposure to MLOps and CI/CD pipelines for model deployment.

- Certifications or project portfolios in Data Science or Machine Learning