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Inspired Capital

Senior Data Scientist

Axion Ray

Axion Ray

Data Science
New York, NY, USA
Posted on Friday, April 12, 2024

Axion Ray’s mission is to improve the quality and safety of innovative, engineered products - airplanes, electric vehicles, medical devices, home appliances, consumer electronics - by creating the world’s best proactive management platform, powered by the latest advances in artificial intelligence. Axion leverages bleeding-edge tech & AI stack to solve real-world problems. With investment from top Enterprise SaaS VCs like Bessemer, and key strategic partners such as Boeing and Raytheon, we are uniquely positioned to solve the hardest problems in manufacturing today. Our team includes experts in Enterprise AI from Palantir, McKinsey & Quantum Black, and other successful Enterprise SaaS companies. Since our founding at the onset of 2021, we’ve deployed across some of the largest manufacturers in the world. If you want the chance to help build the future of manufacturing, join us!

What you'll do:

  • Contribute up and down the stack from data exploration, creating data pipeline, generating insights/features, building ML models to deploying them

  • Support on R&D / discovery pilot projects where we enable clients to understand their data and problems which can be solved using the platform

  • Work closely with a team of ML Engineers, Data Engineers, and Product Managers to build and deploy machine learning models

  • Play an active role in leading team meetings and workshops with clients

  • Rotate between client project work and internal product development in alignment with your personal development plan

  • Work in a hybrid environment based in NYC, along with a team in London

Who you are:

  • 5+ years of experience in a data science role, with a proven track record of developing and deploying predictive models

  • Have previously built insights from ML models, building explainable ML models and not just black box algorithms

  • Demonstrates the ability to make "Data Driven Decisions" and has the ability to communicate why those decisions make sense

  • Excellent communication with technical and non-technical teammates as well as clients. Prior experience in a client facing role will be necessary.

  • Understands the importance of "Data exploration" (in Jupyter notebooks/SQL) as well as building models and setting up data/ML pipelines

  • Is comfortable working in a fast paced, start up environment

  • Proficient in SQL

  • Is comfortable in deploying data/code to the cloud (GCP/AWS)

  • Understands the best practices of collaborative coding using tools like Git, CI/CD

  • Proficient in Python for data science/ML

  • Master of Science or PhD - Data Science or any related field

Nice to have:

  • Experience with MongoDB or other NoSQL DB's

  • Experience working in a startup

  • Experience working with manufacturing companies

Why Axion Ray

  • Join a fast-growing, early-stage startup with the chance to make a significant impact from day one

  • Be part of a world class engineering organization

  • Our culture puts people first - we will encourage you to bring your full self to work and will set you up to succeed

  • Competitive compensation, meaningful equity, and benefits package

  • Career development and leadership opportunities

  • We’re an interdisciplinary team that prizes collaboration & diversity of thinking

  • A chance to make a significant impact in improving the product quality and integrity in the manufacturing space

  • Access to cutting-edge technology and resources

Axion is based in New York, New York with a headquarters in Williamsburg and the team works in a hybrid capacity. This role is expected to work in office at least 3 days weekly.

Axion Ray is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.