Senior Associate at PwC focusing on data analytics to drive insights and guide client strategies. Involves advanced techniques and collaboration on AI and GenAI solutions.
About the role
- Data Scientist designing and deploying ML solutions to improve quality at Ford. Collaborating with engineers and stakeholders to solve impactful business problems through data science.
Responsibilities
- Deliver end-to-end data science solutions: from problem definition, data exploration, and modeling to evaluation and deployment support.
- Translate business needs into solvable data science problems and build consensus on technical approaches.
- Design and execute experiments (e.g., A/B tests) and conduct rigorous model evaluation using relevant metrics.
- Develop, deploy, and monitor production ML models and pipelines using Google Clould Platform (GCP) and MLOps tools (e.g., Kubeflow, MLflow, Airflow).
- Collaborate with cross-functional teams (engineers, analysts, business partners) to ensure solutions are robust, scalable, and aligned with business objectives.
- Write high-quality, reproducible code and contribute to team coding standards and best practices.
- Document data sources, transformations, assumptions, and models clearly for technical and non-technical audiences.
- Stay current with DS/ML trends and proactively share knowledge with the team.
Requirements
- Master’s degree in computer science, Data Science, Mathematics, Engineering, or related field.
- 2+ years of experience delivering impactful data science projects in a business setting.
- Proficiency in Python and SQL; experience with data science libraries (e.g., pandas, scikit-learn, XGBoost, TensorFlow/PyTorch).
- Hands-on experience with GCP and containerization/orchestration tools (Docker, Kubernetes).
- Experience deploying and monitoring ML models in production environments.
- Strong data visualization and communication skills; ability to present findings to varied audiences.
- Experience with version control (Git) and collaborative development workflows.
- Ability to work independently and as part of a team, managing multiple priorities.
- Experience with NLP, LLMs, or advanced ML techniques (e.g., deep learning, anomaly detection).
- Familiarity with MLOps practices and CI/CD pipelines for ML.
- Experience working with large, complex, or multimodal datasets.
- Demonstrated ability to lead small projects or mentor junior team members.
Benefits
- Immediate medical, dental, and prescription drug coverage
- Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and more
- Vehicle discount program for employees and family members, and management leases
- Tuition assistance
- Established and active employee resource groups
- Paid time off for individual and team community service
- A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
- Paid time off and the option to purchase additional vacation time.
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