Staff/Principal Data Scientist Job at Order, New York, NY

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  • Order
  • New York, NY

Job Description

Job Description

Job Description

Company Description

Order.co is a B2B Ecommerce Platform that simplifies purchasing.

Our strength has always been our unique edge: transforming how businesses connect with vendors through our marketplace. We're not just improving workflows - we're redefining how procurement, operations, accounting, and payments come together to drive efficiency and innovation. Every step - requisition, approval, payment, and reconciliation - is curated and automated to make purchasing across all your vendors, locations and teams as easy as purchasing for your personal lives. 

Founded in 2016 and headquartered in New York City, Order.co oversees nearly half a billion dollars in annualized spend across hundreds of customers like WeWork, SoulCycle, and Lume. Order.co has raised $70M+ in funding from industry-leading investors like MIT, Stage 2 Capital, Rally Ventures, 645 Ventures, and more. Order.co has been proudly named as a 50 to Watch by Spend Matters and a Best Place to Work by BuiltIn.

Job Description

We’re looking for a Staff/Principal Level Data Scientist with strong foundations in mathematics and statistics as well as hands-on experience with cutting-edge AI tools to lead transformative data initiatives in the B2B e-commerce space. This role demands previous hands-on experience in Generative and Agentic AI and a deep understanding of neural networks, RAG architecture, and transformer technologies. This role will not only be responsible for technical delivery but also will be accountable for driving business growth through data-driven innovation. 

Staff/Principal level Data Scientists are expected to identify and develop technology solutions to company level objectives, make business cases to secure resources, and successfully launch and scale production projects. Impact should be measured at company level primary KPIs. 

Key Responsibilities

  • Develop and deploy advanced statistical models and machine learning solutions to improve B2B customer experience, pricing optimization, and personalization

  • Work hand-in-hand with the head of data to design and integrate Generative AI and Agentic AI technologies to automate and augment internal and external workflows such as product recommendations, order fulfillment, and customer support

  • Build scalable, end-to-end machine learning pipelines (currently using AWS SageMaker and other AWS services) tailored to high-volume transaction environments

  • Translate sophisticated analytical insights into strategic business recommendations, with a track record of collaborating across teams to implement solutions effectively

  • Design and implement complex stochastic and ensemble models to improve operations and business performance in a variety of functional areas

  • Take action in situations without clear data precedent, balancing the need for academic rigor with a MVP mindset and ability to iteratively deliver DS/AI Models into production

  • Drive experimentation frameworks and A/B testing to validate hypotheses and measure the impact of AI-driven initiatives on revenue and customer retention

  • Mentor and guide data scientists, fostering a culture of innovation and rigorous quantitative analysis

  • Evaluate and incorporate emerging AI technologies and tools to maintain a competitive edge in the fast-evolving B2B and e-commerce landscape

Qualifications

  • Advanced degree (PhD or MS) in Mathematics, Statistics, Data Science, Computer Science, or related quantitative discipline

  • 8+ years of professional experience applying statistical modeling and machine learning in B2B or e-commerce settings

  • Deep expertise in mathematical statistics, causal inference, and experimental design to inform complex business decisions

  • Proven track record of connecting technical work to measurable business results with a focus on revenue growth, customer acquisition, and operational efficiency

  • Comfort with a relatively even split between opportunity identification and hands-on-keyboard execution

  • Proven ability to quickly test and iterate between candidate models with an eye to deploying the right solution that minimizes time to delivery while maximizing the needed performance and reliability metrics

  • Proficient in Python and relevant AI/ML frameworks such as PyTorch, TensorFlow, HuggingFace, and LangChain

  • Practical experience with AWS SageMaker and deploying models in cloud environments optimized for scale and reliability

  • At least 1+ year of hands-on familiarity with Generative AI (e.g., LLMs, diffusion models) and Agentic AI systems tailored for internal and/or customer-facing applications

  • Strong communication skills with experience collaborating with sales, marketing, product, operations, and engineering teams to drive business impact

  • Experience with vector search databases, RAG systems, and AI orchestration for personalized content and recommendation engines

Additional Information

What you'll receive

  • You'll be at the forefront of AI innovation powering scalable B2B commerce and next-generation e-commerce experiences
  • The chance to collaborate with a passionate, cross-disciplinary team dedicated to driving measurable business outcomes
  • A competitive compensation package including equity and comprehensive benefits
  • Flexible time off and remote work policies
  • Medical, dental, vision, and 401(k) with match
  • A fast-paced and collaborative team environment

The anticipated base annual salary for this role is $205,000-$235,000 with the opportunity for meaningful equity grants. Actual compensation and title will be commensurate with experience, qualifications, knowledge, and skills.

Order.co is an equal-opportunity employer. Applicant's qualifications are considered without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, veteran status, genetic information, or any other basis prohibited by law.

Job Tags

Remote work, Flexible hours,

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