Easy Apply
Easy Apply
Work with simulation and ML engineers and customers to preprocess data, build and deploy deep learning and probabilistic predictive models, design scalable data pipelines, integrate models with simulations, and present solutions to technical stakeholders. Frequent customer-site collaboration and product development to ensure practical, production-ready outcomes.
About us
Who We're Looking ForPhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.
We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
As a Data Scientist in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to transform cutting edge AI models into tools that are useful and used.
You’ve worked on difficult problems that require strong foundations in data driven modelling and deep learning techniques, with hands-on experience in probabilistic methods and predictive modelling. Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production-ready models and data pipelines.
With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of data science work streams, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
In this role, you’ll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving.
You’ll build the foundations for successful, impactful solutions by:
- Pre-processing and analyzing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.
- Developing and utilizing innovative deep learning models in combination with state-of-the-art optimization methods to predict and control the behaviour of physical systems.
- Taking full responsibility for the quality, accuracy and impact of your work.
- Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
- There is a requirement to travel to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you’ll collaborate closely with customers to build solutions on site.
As the role evolves, there are exciting opportunities for growth as an individual contributor or a technical lead, especially if you’re driven by taking ownership of more complex projects and leading the direction of future solutions.
Please note, this role is based in Manhattan, NYC, working 2-3 days per week in our office.
- Equity options – share in our success and growth.
- 5% 401(k) match – invest in your future.
- Flexible working – balance your work and life in a way that works for you.
- Hybrid setup – enjoy our Manhattan office while keeping remote flexibility.
- Enhanced parental leave – support for life’s biggest milestones.
- Private healthcare – comprehensive coverage for you and your family.
- Personal development – access learning and training to help you grow.
- Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.
We believe diversity fuels innovation, and we're building a culture where everyone belongs. We're proud to be an equal opportunity employer, welcoming talent of all backgrounds, identities, and experiences. Changing the face of tech takes action, which is why we actively encourage individuals from historically underrepresented groups to apply.
Salary Range
$120,000 - 240,000 depending on experience
Seniority will be assessed throughout our interview process
Seniority will be assessed throughout our interview process
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. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
Top Skills
Python,Numpy,Scipy,Pandas,Tensorflow,Pytorch
PhysicsX New York, New York, USA Office
2nd Floor 154 W 14th Street, New York, NY, United States, 10011
Similar Jobs
Fintech • Machine Learning • Payments • Software • Financial Services
Lead model risk audits by reviewing model development, validation, and implementation; partner cross-functionally to build and evaluate ML/NLP solutions using Python, Spark, H2O, and AWS; translate technical findings into business risk insights and drive model risk governance.
Top Skills:
Python,Conda,Aws,H2O,Apache Spark,Sql,Scala,R,Relational Databases,Nlp,Generative Ai,Machine Learning,Deep Learning
Artificial Intelligence • Healthtech • Logistics • Social Impact • Software • Telehealth
The role involves analyzing healthcare data to optimize care delivery, predict patient needs, and support internal teams through insights, dashboards, and A/B testing.
Top Skills:
BigQueryDataflowDataformElasticsearchGrafanaKibanaLookerPandasPythonRedshiftScikit-LearnSnowflakeSQLSupersetTableau
Fintech • Machine Learning • Payments • Software • Financial Services
As a Principal Associate, Data Scientist, you will lead fraud detection strategies using machine learning and collaborate with cross-functional teams to enhance fraud models and deliver innovative solutions.
Top Skills:
AWSCondaH2OPythonSparkSQL
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
