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Data Scientist

Work from home Full-time role Hiring

About Nooks.ai:

Nooks is the AI Sales Assistant Platform (ASAP) that automates the busywork so reps can focus on the human part of selling and generate more sales pipeline. Nooks has helped thousands of sales reps hit quota, saved customers hundreds of thousands of hours, and powered hundreds of millions of dollars in pipeline. Nooks is loved by sales teams at companies like 1Password, Fivetran, Greenhouse, and hundreds more. For more information, visit Nooks.ai.

The role

Note: Exact job title will be commensurate with experience

We have an ambitious product vision in a nascent area - AI-powered realtime collaboration - so there are a ton of interesting technical challenges on our roadmap. This is a role focused on full-funnel insights from sales data. You'll play a pivotal role in driving key decisions and building a data-driven culture at Nooks.

Examples of engineering problems you may touch

These are just examples, this list is non-exhaustive, and you definitely don’t need experience in all of these areas. But hopefully you find some of them exciting!

  • Optimizing call connection rates

    • Sales reps use Nooks to connect with prospects over sales calls. These connections may be successful based on a wide variety of factors - where the sales rep is calling from, when they call, data quality, prior interactions. How do we extract insights from our data to make sales reps and teams using Nooks more productive by maximizing their connection rate?

  • Conversation funnels & markov models (data science/modeling)

    • What does the anatomy of a call look like? If I say XYZ, what are the different ways the prospect might answer and the probabilities of each? Conditioned on the first half of the call, what does Nooks need to recommend to maximize the likelihood that a sales rep books a demo at the end of the call?

  • Lead scoring and account insights

    • Nooks surfaces leads that we think are a good fit to reach out to with first-touch emails and calls. We do this using AI "deep research signals." Which signals are actually most likely to lead to good outcomes for the business (i.e converted revenue) and how do we use leading indicators and small amounts of data to prioritize the prospects that have the highest expected value of converting to revenue?

Requirements
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.

  • Expert in SQL and Python or R

  • 3+ years of industry experience

  • Robust understanding of statistical and machine learning methods

  • Full stack eng chops: reasonable proficiency in general purposes programming languages such as Python/Javascript, and with libraries like pandas, scikit-learn etc.

Nice to haves
  • Background in an analytical field like heuristics, data science &/or statistics

  • Prior experiences working in both startup and research environments

  • Experience with data transformation and data orchestration tools

We offer competitive compensation because we want to hire the best people and reward them for their contributions to our mission. We pay all employees competitively relative to market. In compliance with pay transparency laws and in pursuit of pay equity and fairness, we publish salary ranges for our open roles. On top of base salary, we also offer equity, generous perks and comprehensive benefits.

Equal Employment Opportunity Statement

Nooks is an equal opportunity employer committed to fostering a diverse and inclusive workforce. We believe in providing equal employment opportunities to all individuals regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other characteristic protected by law.

Nooks does not discriminate in hiring, promotion, compensation, or any other employment practices, and we are committed to ensuring a workplace that is free from discrimination, harassment, and retaliation. We encourage individuals from all backgrounds to apply and join our team.

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