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Job Description: Data Scientist Manager (PwC US AC)

PwC US Acceleration Center is seeking a highly skilled and experienced Data Scientist to join our team at the Manager level. As a Data Scientist, you will play a critical role in designing, developing, and deploying predictive models, statistical analyses, and AI-driven solutions that transform complex data into actionable business insights.

The ideal candidate should have a strong background in data science and machine learning, hands-on experience in model development and deployment, and the ability to collaborate with cross-functional teams to deliver scalable analytics solutions across industries.

Responsibilities:

- Collaborate with business stakeholders to understand problem statements and translate them into analytical solutions.
- Design, develop, and deploy predictive models including classification, regression, clustering, and time-series forecasting models.
- Perform exploratory data analysis (EDA), data cleaning, preprocessing, and feature engineering on structured and unstructured datasets.
- Apply statistical techniques including hypothesis testing and experimental design to validate insights and model performance.
- Work closely with data engineers to build and maintain scalable data pipelines and ensure efficient data processing.
- Deploy machine learning models into production environments using APIs and containerization technologies.




- Implement MLOps best practices including model versioning, monitoring, CI/CD integration, and model registries.
- Utilize cloud platforms such as Azure, AWS, or GCP for model training, deployment, and scaling.
- Develop interactive dashboards and visualizations using tools such as Power BI, Tableau, Matplotlib
- Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data storytelling.
- Stay updated with the latest advancements in machine learning, AI, and data science methodologies to drive innovation.

Requirements:

- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
- 7+ years of relevant experience in data science, machine learning, or applied statistics.
- Strong programming proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and/or R.
- Experience building and validating predictive models (classification, regression, clustering, time-series).
- Strong understanding of statistics, hypothesis testing, and experimental design.
- Proficiency in SQL and experience working with structured and unstructured datasets.




- Hands-on experience with machine learning frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
- Experience deploying ML models into production using FastAPI or similar frameworks.
- Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
- Experience working with cloud platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI.
- Experience with Spark (PySpark), Databricks, or large-scale data processing frameworks.
- Knowledge of MLOps tools such as MLflow, model registries, and CI/CD pipelines.
- Experience working with SQL/NoSQL databases, Data Lakes, and Blob Storage.
- Robust analytical, problem-solving, and communication skills.
- Ability to work in a fast-paced and dynamic environment.

Nice to Have Skills:

- Experience working on AI/LLM-enabled analytics solutions.
- Exposure to Generative AI or advanced AI frameworks.
- Experience in building data products or end-to-end ML platforms.(pandas,Keras, Tensorflow)
- Relevant certifications in Data Science, Cloud, or Machine Learning technologies.
- Strong background in the Healthcare domain, with deep understanding of Payer operations and working knowledge of Provider ecosystems.
- Experience in consulting engagements, including direct interaction with client stakeholders and managing client relationships.
- Demonstrated leadership experience managing and mentoring teams of 5–10 members.

Preferred Qualifications:

- BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Master’s Degree / MBA from a reputed institute

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