Applied Analytics & ML Product Builder

Orbia

2d

About The Position

This role is designed to build practical, low-overhead analytics and ML/AI tools that support decision-making and productivity across OFEM functions, while simultaneously raising internal analytics fluency and helping the organization learn where advanced analytics can (and cannot) realistically scale. This is not a large‑scale automation role or a centralized AI helpdesk. Instead, it is a hands‑on, product-oriented builder role focused on rapid learning, transparent constraints, and durable value. The role acts as a seed capability, generating evidence to guide future analytics organization design.

Requirements

• Bachelor’s degree in a technical field (Chemical Engineering strongly preferred)
• Master’s degree or equivalent training in Data Science, Analytics, or a related field
• Comfort working hands-on with data, code, and analytical tools
• Ability to understand business and technical problems before jumping to solutions
• Strong communication skills, and willingness to teach and document work clearly

Nice To Haves

• Exposure to manufacturing, R&D, or industrial data
• Experience during internships or projects demonstrating practical impact

Responsibilities

• Builds practical, high‑impact analytics and decision‑support tools across R&D, Manufacturing, Quality, Supply Chain, Finance, and Strategy/BI, with a strong emphasis on clarity, insight, and improved decision‑making rather than automation for its own sake.
• Curates and structures data from existing sources—including reports, dashboards, exports, LIMS summaries, and historian aggregates—to enable faster, more reliable analysis.
• Develops proofs of concept, from rapid, low‑friction tools that generate near‑term learning and time savings (e.g., internal BI or document search and summarization tools, trend and variability analysis for plant, QC, cost, or R&D data, and simplified data structures for recurring calculations such as cost or P&L rollups), to deeper exploratory efforts that assess where advanced analytics could scale (e.g., energy and throughput trade‑off analysis tools, early‑warning or root‑cause exploration combining plant, quality, and deviation data, or structure–property relationship analysis for electrolyte molecules).
• Applies machine learning, optimization, or predictive methods selectively and pragmatically, where they provide meaningful incremental insight.
• Executes all work transparently within known data access, quality, and system limitations, with clear documentation of assumptions, data gaps, access challenges, and scalability constraints.
• Shares learnings and practices with peers by collaborating closely with domain experts, co‑building tools to improve usability and adoption, participating in informal knowledge‑sharing sessions, offering ad‑hoc guidance during office hours, and contributing to lightweight internal guides or playbooks.
• Collaborates closely with IT, BI, and enterprise digital teams to ensure continuity and supports transition of durable tools once stabilized; it does not own production systems long‑term.
• Prioritizes work with guidance from a small AI/Analytics alignment group representing business units and functions.
• Spends approximately 70% of time on hands‑on analytics and tool building, 20% on teaching and coaching, and 10% on coordination, learning, and transition planning.

Benefits

• Equal opportunity employer
• Consideration for employment without regard to race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 and over), national origin or ancestry, citizenship status, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed service member status, or any other status protected by federal, state or local law.
• Affirmative Action Program (AAP)
• Reasonable accommodation for applicants with disabilities under the terms of the Americans with Disabilities Act and certain state or local laws.
• Protection under Federal law from discrimination on protected grounds.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level