As our Founding Data Scientist, you’ll own Response’s data science pipelines and help build the world’s largest structured B2B product database. Beyond building new models, you’ll also play a foundational role in establishing and leading our Data Science team - including setting culture, hiring, and managing.
Why now?
We’re scaling our dataset to 40M B2B products and need support to make that data useful.
Responsibilities
Below you can find the set of responsibilities that serve as the basis for the role:
(1) Develop cutting-edge information retrieval and NLP systems to solve challenges like:
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Categorization: categorizing products from different vendors into one hierarchy
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Specification matching: extracting and normalizing product specifications
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Similarity: using clean specification data to determine whether two products are the same or variants
(2) Owning Response’s data science pipelines
- Leading projects from start to finish, including initial scoping, design, data modeling, implementation, and testing
- Collaborating closely with the founders and team across functions to determine and refine long-term engineering roadmap
- Familiarizing yourself with our existing pipelines and identifying new techniques and optimizations to improve performance
(3) Growing and leading our Data Science team
- Helping to establish and lead a world-class data science and engineering team
- Setting our data science and engineering team culture
- Formalizing our data science stack and documentation
Once you’re onboarded, we’ll work together to refine these outcomes to make them measurable and time-bound. We’ll also create a set of learning outcomes that align with your personal and professional growth goals.
What we’re looking for
- Solid production experience in developing and implementing data pipelines
- Ability to work with a diverse dataset that includes image, unstructured, and structured data
- Experience with NLP, data cleaning, and categorization techniques
- Demonstrated ability to build reliable supervised and unsupervised ML methods, be it in a professional setting or side project
- Familiarity with reinforcement learning
- Flexibility - able to switch directions quickly and learn the necessary skills to tackle unique challenges
- Experience with hiring, managing, and scaling engineering teams
- Have led a team of data scientists in implementing technology in production
- Independence - thrives in ambiguity and can work autonomously
What excites us
These are not requirements - it simply isn’t realistic to expect all of these from one person. We would be delighted even if you have just one or two.
- Experience with machine learning frameworks such as PyTorch, Tensorflow, etc.
- A strong track record of building interesting projects.
- Experience developing models within an eCommerce setting.
- Previous founding or startup experience.
- Realistic problem-solving approach - thoughtfully considers the tradeoffs between speed and polish to achieve the “90/10” solution.
- Awareness of real-world impact - realize that we have an impact on the users, businesses, and stakeholders who interact with our technology.
- Genuine curiosity and desire for feedback.
Our Data Science stack
We use a variety of tools/languages/technologies at Response for Data Science. We don’t strictly require experience in any of them, but here’s our primary stack:
- Python
- PyTorch
- Paperspace
- Pandas
- SK-Learn
- AWS
Benefits
- Equity
- Health & Dental insurance
- Flexible PTO / Time-off
- Flexible wellness stipend
- WFH equipment budget
- Remote friendly workplace
- Offsite company trips
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you feel like you don’t meet every requirement for this role, we encourage you to apply anyways. We’re flexible and don’t want technicalities getting in the way of meeting incredible candidates.
Response
