Machine Learning Senior Computer Scientist

Title:

Machine Learning Senior Computer Scientist

BELONG. CONNECT. GROW. with KBR.

Around here, we define the future. We are a company of innovators, thinkers, creators, explorers, volunteers, and dreamers. But we all share one goal: to improve the world responsibly and safely.

This position focuses on leading and managing teams to leverage machine learning (ML) and deep learning (DL) techniques in addressing complex challenges across various domains, with a primary emphasis on astronomy and space science.

The role involves guiding the development and deployment of ML/DL methodologies for high-impact applications such as the detection, validation, and characterization of exoplanets using data from missions like Kepler, TESS, and JWST. Additionally, it requires strategic oversight in extending these technologies to tackle broader scientific and technical challenges, fostering innovation and collaboration across multidisciplinary teams. This leadership role is instrumental in advancing the use of ML/DL technologies, shaping the future of data-driven discovery, and achieving mission objectives through effective management and vision.

Job Description:

• Manage a team of data scientist and machine learning working on design, develop, and test advanced ML/DL models for applications such as exoplanet transit classification, anomaly detection, and data analysis, with a particular focus on astronomical datasets from Kepler, TESS, and JWST.
• Task lead management duties: ensuring milestones/deliverables are properly managed, responding to task modifications with changes in requirement scope, and regularly meeting with the customer to make sure the quality, schedule, and budget is in line with the customer’s scope and expectations.
• Create software tools and pipelines to integrate ML/DL solutions into scientific workflows, ensuring high accuracy, interpretability, and scalability for diverse datasets.
• Build simulations, synthetic datasets, and test cases to validate and benchmark ML/DL models under various conditions, including noise and data sparsity, ensuring their robustness and reliability.
• Apply ML techniques to interdisciplinary problems, such as fault management, anomaly detection, and signal processing, to support broader space science and engineering missions.
• Collaborate with experts across disciplines, including astrophysics, engineering, and data science, to align ML solutions with scientific and technical objectives.
• Contribute to the preparation of mission-critical reviews and evaluations by developing tools for data analysis, validation catalogs, and statistical assessments tailored to specific mission needs.
• Stay current with advancements in ML/DL and explore their application to emerging challenges in space science and beyond.
• Write and contribute to scientific publications and research proposals, effectively communicating findings, methodologies, and innovations to advance mission objectives and secure funding.

REQUIRED Skills and Traits:

• Ph.D. in Computer Science, or related field, with 19 years of experience.
• Technical Expertise: Strong background in machine learning (ML) and deep learning (DL), with hands-on experience applying these techniques to real-world problems, particularly in astronomy and space science. Proficiency in data analysis, model development, validation, and optimization.
• Domain Knowledge: Familiarity with astronomical datasets, including those from missions like Kepler, TESS, and JWST. Understanding of exoplanet detection techniques, transit photometry, and related scientific methodologies.
• Analytical Thinking: Ability to assess complex problems, identify critical risks, and develop innovative solutions for mission-critical applications. Skilled in creating simulations, "what-if" scenarios, and diagnostic models to support mission operations.
• Collaborative Leadership: Demonstrated experience working with multidisciplinary teams, including scientists, engineers, and project managers. Strong interpersonal skills to lead discussions, facilitate collaboration, and build consensus.
• Communication Skills: Proficiency in translating complex technical concepts into clear, concise documentation and presentations for diverse audiences, including stakeholders, operators, and reviewers.
• Problem-Solving: Experience in risk management, anomaly response planning, and contingency procedure development. Ability to design and implement fault-tolerant systems and troubleshoot issues effectively.
• Adaptability and Initiative: Proven ability to manage multiple priorities, adapt to evolving project needs, and take initiative in driving projects to successful completion.

Basic Compensation:

$184,100.00 – $27