Lead Data Scientist driving ML and data science initiatives for advertising technology at Disney. Collaborating with a team to enhance ad decisioning and user experience optimization with generative AI.
About the role
- Data Scientist designing, developing, and executing machine learning models for PG&E’s electric operations. Collaborating with various departments to solve complex strategic issues and enhance decision-making.
Responsibilities
- Designs, develops, and executes scripts, programs, models, algorithms, and processes using structured and unstructured data.
- Participates in internal and external communities of practice in data science/artificial intelligence/machine learning.
- Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.
- Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
- Solves unique and complex strategic issues and problems while developing and monitoring budgets, forecast models, dashboards, presentations, and ad hoc analysis.
- Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies.
- Extracts, transforms, and loads data from dissimilar sources.
- Applies data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive models.
- Wrangles and prepares data as input of machine learning model development and feature engineering.
- Writes and documents reusable python functions and modular python code for data science.
- Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, and analytic procedures.
Requirements
- Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
- 6 years in data science OR no experience, if possess Doctoral Degree or higher, as described above.
- Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience.
- Active participation in the external data science/artificial intelligence/machine learning community of practice.
- Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc.)
- Knowledge of industry trends and current issues in job-related area of responsibility.
- Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms.
- Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
- Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders.
- Mastery of the mathematical and statistical fields that underpin data science.
- Ability to develop, coach, teach and/or mentor others to meet both their career goals and the organization goals.
Benefits
- PG&E’s discretionary incentive compensation programs
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Science and AI student engaged in data processing and management. Open to candidates in Germany, starting in 2026, with supportive environment for development.
Data Scientist II providing actionable insights through advanced analytics and consulting with stakeholders at Truist. Conducting statistical analyses and developing predictive models using structured and unstructured data.
Senior Responsible AI Data Scientist focusing on ethical AI within Humana to drive responsible AI initiatives across the organization. Partnering with teams to implement innovative and compliant AI solutions in healthcare.
Director of Data Science leading the Identity fraud product development at TransUnion. Collaborating with stakeholders to build market - leading identity data products and analytic solutions.
Data Analyst supporting internal audit for a bank in Zürich. Building databases, conducting analysis, and presenting findings to senior management.
Manager II, Data Science leading HR Analytics and developing predictive models for decision - making. Collaborating with cross - functional teams to implement data - driven solutions across the organization.
Data Manager for B2B - Mailings at ZEIT Advise, supporting the automation and segmentation of marketing processes in Hamburg. Focusing on CRM systems and email marketing strategies.
Lead Data Scientist at AT&T, building predictive models and analyzing customer lifecycle marketing strategies. Collaborating with cross - functional teams to enhance marketing and business outcomes.
Lead Data Scientist managing AI initiatives for a global IT consulting firm. Overseeing AI strategy, governance, and multidisciplinary team leadership in a hybrid work environment.