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About the Role

As a Data Scientist in Delivery, you will solve complex engineering problems by building practical AI-driven solutions. You will work directly with customers to transform cutting-edge AI models into actionable tools, bridging the gap between advanced numerical physics and real-world engineering applications.

Responsibilities

• Pre-process and analyze data for predictive modeling.
• Develop deep learning models and optimization methods to predict and control physical systems.
• Take full responsibility for the quality, accuracy, and impact of work.
• Design, build, and test reliable, scalable, and production-ready data pipelines.
• Collaborate with simulation engineers to integrate data science models with simulations.
• Contribute to internal R&D and product development.
• Engage in technical communication and presentations with customers.
• Travel to customer sites globally for approximately 3-4 weeks per quarter.

Requirements

• Strong foundation in data-driven modeling and deep learning techniques.
• Hands-on experience with probabilistic methods and predictive modeling.
• At least 1 year of industry experience in a commercial, non-research environment.
• Ability to deploy scalable, production-ready models and data pipelines.

Skills

• Python
• NumPy
• SciPy
• Pandas
• TensorFlow
• PyTorch

Location

• New York, USA

Work Type

• Hybrid

Experience Level

• Post-Masters or PhD with at least 1 year of industry experience

Education Level

• Masters or PhD

Salary/Compensations

• $120,000 - $240,000

Benefits

• Equity options
• 5% 401(k) contribution
• Free team lunch 1x/week
• Private health insurance
• Enhanced parental leave (3 months full pay paternity, 6 months full pay maternity)
• 20 days of annual leave plus public holidays
• Personal development support
• Subsidized Gympass / Wellhub
• Flexible Spending Account (FSA)

About the Company

• Deep-tech company with roots in numerical physics and Formula One.
• Building an AI-driven simulation software stack for engineering and manufacturing.
• Customers include leaders in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

Equal Opportunity

• We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity.
• We strongly encourage individuals from groups traditionally underrepresented in tech to apply.