Jobs / United States / Castrol
Pricing Data Science & Automation Manager
Castrol · 🇺🇸 Location unlisted
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — Castrol
This employer posted directly and does not match a government sponsor register.
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About the role
Castrol is one of the world’s leading lubricant brands, serving customers and consumers in the automotive, marine, industrial and energy sectors. Castrol brands are recognised globally for their premium quality and high performance, shaped by the company’s commitment to innovation and cutting-edge technology. With products sold in more than 150 countries, Castrol has helped keep things moving on roads and racetracks, air, sea, and space for over 125 years. Whether you're just starting out or ready for your next big move, you're in the right place to explore an exciting career with Castrol. Job description About the team You'll join Castrol's Global Pricing team, reporting to the Global Strategic Pricing Manager and leading a small team of data scientists and analysts. Working alongside colleagues with pricing and commercial expertise, you'll combine technical problem-solving with developing others, turning your team's analysis into decisions that improve revenue, margin and product mix. Key tasks Which pricing questions are worth solving, and how do you turn the answers into something the business can use? You'll help connect the commercial problem, the analytical approach and the practical solution. • Find where margin is being lost across discounts, rebates and trade investments. Quantify the opportunity, recommend corrective action and support governance of pricing corridors, floors and exceptions. • Help the business make better product-price-pack and portfolio choices across DIY, DIFM and B2B channels. Explore customers, segments, specifications, pack sizes and tiers to inform price positioning and the price steps between offerings. • Develop and deploy models for elasticity, demand forecasting, willingness to pay, price sensitivity, scenarios and price optimisation, translating the results into recommendations people can act on. • Turn recurring work into repeatable tools. Design automation for price changes, analysis, reporting and decision support, reducing manual intervention and making solutions usable across markets. • Lead and develop your analytical team, encouraging commercial curiosity and innovation. Set priorities around business value, plan projects and help colleagues turn their technical work into practical outcomes. • Partner with Pricing, Sales, Finance and Marketing, using clear explanations of the evidence to influence senior stakeholders and connect analytical findings to commercial decisions. Success means more than delivering a model: it means measurable commercial impact, pricing processes that need less manual effort, and a team that understands its priorities and develops its capabilities. Experience required You don't need a long management career behind you. You'll need technical depth, evidence that your analysis makes a difference, and the aptitude to help others do their best work. • A university degree or higher, with proven experience in pricing analytics, data science or operations research, ideally in a commercial environment. • Strong mathematical and statistical modelling skills, including regression, machine learning and segmentation, and the ability to apply them to questions such as demand forecasting, elasticity and price optimisation. • Proficiency in analytical tools such as Python, R and SQL and visualisation platforms such as Power BI or Tableau, with experience working with large datasets and building scalable solutions. • Evidence of translating analysis into business impact, supported by commercial judgement, problem-solving and decision-making skills. • The ability and aptitude to lead and develop a small analytical team. Previous leadership or mentoring experience is valuable, but strong technical candidates with less management experience will also be consi