Senior AI/ML scientist in Computational Toxicology driving advanced AI/ML solutions for safer drug discovery and regulatory methodologies.
About the role
- Lead Principal Data Scientist at Volkswagen Financial Services focusing on data science product development and leading high-impact initiatives. Collaborate to shape VWFS’s mobility transformation strategy with data-driven solutions.
Responsibilities
- Lead data science product development, set standards, best practices, and innovation for the data science CoE (25%)
- Experimentation, build, integration of data science solutions into core business processes and new opportunities (75%)
- Definition and ongoing improvement of a machine learning environment
- Develop and deploy AI models that impact business decisions
- Establish best practices and governance routines to ensure adherence to model management policies, peer reviews, and compliance to our policy standards for privacy, ethics, and bias.
- Bring relevant data science techniques, algorithms, and tools to your team
- Provide technical oversight, help and mentorship to the junior data scientists on the team
- Apply suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness
- Innovate new ML methods in the data science space and drive change throughout the business
- Contributes to code documentation, maintains playbooks, and provides timely progress updates
- Help generate compelling hypotheses to drive new business creation
Requirements
- Bachelor’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field
- Master’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field
- 12+ years of data & analytics work experience with 8+ years in data science
- 7+ years in utilizing methods and tools to extract, curate, explore, and analyze data from large data sources
- 7+ years in developing, integrating and deploying machine learning solutions into the business decision making process
- 7+ years in leveraging algorithms, tune parameters and back testing validation
- 5+ years leading ML project development
- Collaborate with product owners and product managers to translate business requirements into impactful AI solutions that scale
- Build, integrate and deploy machine learning solutions into the business decision-making process
- Thorough knowledge of machine learning models, including both traditional ML and GenAI
- Utilize a consultative approach to work with the business to solve challenging problems using various analytical techniques
- Embrace, research, explore, and enable new quantitative techniques and technologies in data science that will help define VWFS as an industry leader in the application of data science techniques
- Extensive experience with model evaluation and solid grasp of A/B testing and causal analysis
- Research new data sources and analytical tools, contribute to new application development, and data quality improvement efforts
- Ability to originate curiosity to collaborate with different business units to co-create solutions
- Passion for data analysis and problem solving
- Establishes and maintains effective performance tracking; identifies improvement opportunity, form hypothesis, propose, design and implement tests to drive strategy enhancement and optimization.
- Superior ability to communicate technical ideas and results to non-technical users in written and verbal form.
Benefits
- Unknown
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