About the Role
As a Digital Science Associate, you will connect powerful scientific advancements with real-world business opportunities. Working across artificial intelligence, data science, sophisticated analytics, and computational modeling, you will explore new directions that can bring value for bp and support its digital transformation.
In this position, you will establish relationships with government organizations, startups, and industry partners. Together with these collaborators, you will help shape research initiatives, explore new insights, and uncover opportunities that could benefit bp's businesses.
You will coordinate proof-of-concept activities from early exploration through implementation, partnering with technical, commercial, and legal teams to support informed decision-making and successful delivery.
Success in this role comes from a combination of technical expertise, curiosity, collaboration, and sound judgment.
What You Will DeliverTechnology Scouting and Evaluation- Identify, assess, and prioritize emerging digital, AI/ML, and computational technologies that have the potential to address strategic business challenges.
- Supervise academic, industrial, and commercial technology landscapes to identify relevant innovation opportunities.
- Evaluate technology maturity, scalability, business relevance, and deployment readiness.
- Develop independent technical assessments and recommendations regarding the adoption of new technologies.
External Partnerships and Innovation- Establish and lead partnerships with organizations.
- Define collaboration scopes, structure partnership agreements, and be a phenomenal partner.
- Serve as a representative for bp across external innovation engagements.
- Build and maintain a portfolio of external partnerships that supports bp's innovation and research objectives.
Proof-of-Concept Leadership- Lead proof-of-concept (PoC) projects from initiation through completion.
- Define objectives, success criteria, timelines, and key results.
- Coordinate research agreements, contracts, intellectual property considerations, and interested party alignment.
- Assess project outcomes and provide data-driven recommendations regarding future development, scaling, or adoption.
Technical Assessment and Strategy- Benchmark emerging technologies against existing bp workflows, industry standards, and relevant technical baselines.
- Assess data quality, availability, scalability, and model performance.
- Identify mitigation strategies for data and modeling limitations, including transfer learning, synthetic data generation.
- Evaluate the commercial viability and business impact of emerging technologies.
Technology Deployment- Support the transition of validated technologies into bp's business and technology organizations by collaborating with engineering, operations, and digital teams.
- Define deployment pathways and facilitate effective technology handover.
- Work with relevant collaborators to ensure successful implementation and value realization.
Government and Research Ecosystem Engagement- Engage with organizations such as the National Science Foundation (NSF), Department of Energy (DOE), ARPA-E, and laboratories to identify collaboration and funding opportunities.
- Supervise research initiatives and emerging opportunities.
- Support or lead proposal development activities.
Executive and Interested party Communication- Prepare executive-level briefings, technology reviews, and recommendations.
- Communicate sophisticated technical topics optimally to both technical and non-technical audiences.
- Support long-term technology strategy development and innovation planning.
- Present proof-of-concept outcomes and technology assessments,
Knowledge Sharing- Document project outcomes, lessons learned, and guidelines.
- Develop reusable frameworks and methodologies for evaluating emerging technologies.
- Supply to the broader Digital Science innovation agenda by sharing insights from the external technology ecosystem and identifying emerging opportunities.
What You Will Need to Be SuccessfulEducation- Master's degree or equivalent experience in Computer Science, Data Science, Applied Mathematics, Physics, Chemical Engineering, Mechanical Engineering, Computational Science, Engineering, or a related technical field.
- PhD or equivalent experience research experience is highly preferred.
Technical ExpertiseSolid understanding of Artificial Intelligence and Machine Learning, including:
- Machine Learning
- Deep Learning
- Probabilistic Modeling
- Scientific Machine Learning (SciML)
- Physics-Informed Neural Networks (PINNs)
- Operator Learning
- Hybrid Modeling
- Optimization Techniques
- Uncertainty Quantification
Ability to critically evaluate technical research, validate results, and assess technology readiness and scalability.
Experience benchmarking models, evaluating performance claims, and assessing technical maturity.
Understanding of modern computational science methodologies and digital technologies.
Experience- Significant experience leading external research collaborations and technology partnerships.
- Experience handling proof-of-concept initiatives and technology evaluations from concept through completion.
- Experience working with universities, national laboratories, government research organizations, startups, or technology vendors.
- Familiarity with research agreements, intellectual property considerations, and collaborative research frameworks.
- Experience engaging with government-funded research programs and agencies such as NSF, DOE, ARPA-E, or national laboratories.
- Validated experience assessing emerging technologies and translating technical findings into business recommendations.
Leadership and Communication- Exceptional written, verbal, and presentation skills.
- Validated experience presenting technology assessments and strategic recommendations to senior leadership.
- Strong collaborator management and relationship-building capabilities.
- Ability to operate efficiently in ambiguous environments and make informed decisions under uncertainty.
- Strong influencing skills to navigate sophisticated organizational and external interested party environments.
Additional Capabilities- Understanding of intellectual property management in collaborative research environments, including ownership, licensing, publication rights, and data-related considerations.
- Strong project management and organizational skills, with the ability to handle multiple concurrent initiatives and partnerships.
- High commercial awareness, professional integrity, and sensitivity to confidential information.
- Curiosity and passion for new technologies and their application to scientific and engineering challenges.
- Strong analytical and problem-solving capabilities with a continuous learning attitude.
Travel Requirement
Up to 10% travel should be expected with this role
Relocation Assistance:
This role is not eligible for relocation
Remote Type:
This position is not available for remote working
Skills:
Commercial Acumen, Communication, Data Analysis, Data cleansing and transformation, Data domain knowledge, Data Integration, Data Management, Data Manipulation, Data Sourcing, Data strategy and governance, Data Structures and Algorithms (Inactive), Data visualization and interpretation, Digital Security, Extract, transform and load, Group Problem Solving
.