Data Scientist Jobs

About The Position

Requirements

• 5+ years of professional experience in developing and deploying AI/ML solutions, with a strong emphasis on Generative AI technologies and a solid background in applying these methods to physical systems and engineering workflows.
• Deep expertise in natural language processing (NLP), large language models (LLMs), and building agentic workflows for Generative AI with the ability to understand underlying mathematics and develop novel algorithms.
• Solid understanding of knowledge graphs, ontologies, and semantic technologies.
• Solid foundation and experiences in AI/ML on data processing, probability and statistics, EDA, feature engineering, modeling strategy, model development, and explainable AI.
• Proven track record of successfully developing and deploying multiple end-to-end Generative AI solutions, notably multi-agent systems, in business environments.
• Proficient in Python and widely used ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Proficient in Generative AI frameworks such as Langchain, Promptflow, or Copilot Studio.
• Proven ability to uncover meaningful insights from complex datasets.
• Strong drive toward hands-on testing of hypotheses and rapid validation of assumptions through data.
• Strong communication, collaboration, and problem-solving skills.
• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Engineering, or a related field.

Nice To Haves

• Experience in the energy industry, preferably with a focus on subsurface or well-related topics.
• Experience in implementing hybrid search systems in conjunction with Large Language Models, e.g. Retrieval Augmented Generation (RAG) solutions.
• Proficient in using the Databricks platform, Azure Open AI, Azure managed NLP services and OCR technologies.
• Demonstrated ability to thrive in a collaborative Agile product team setting.

Responsibilities

• Lead the scoping, design, development, and deployment of AI/ML solutions, primarily focused on Generative AI applications for subsurface and well-related operations.
• Collaborate with data and machine learning engineers to operationalize models and ensure seamless integration with existing digital infrastructure.
• Build and deploy AI system components (such as chatbots, agents, and other workflow automation components) capable of interacting with diverse data sources and providing insightful information to users.
• Develop and implement solutions involving orchestration of multiple AI agents to achieve complex tasks.
• Apply domain knowledge and physical principles to improve model accuracy and reliability.
• Contribute to the growth of internal AI capabilities by sharing expertise and developing best practices.
• Provide technical mentorship and guidance to colleagues across teams.
• Work closely with team leads and subject matter experts to align on project priorities, strategy, and solution design.
• Optimize end to end AI solutions to enhance performance, usability, and cost.
• Work closely with business to understand business problem and translate that into mathematical framework. Also, work with business to help enhance business adaptability for the solution.
• Validate AI system responses, including troubleshooting prompt engineering, agentic workflows and other aspects of a GenAI system.
• Develop process and automation for accelerating validation of AI systems, while ensuring the proper degree of accuracy is maintained.

Benefits

• Pension Plan
• Savings Plan
• Workplace Flexibility
• Comprehensive medical, dental, and vision plans.
• Culture of Health
• Employee Health Advisory Program
• Disability Plan