Senior Data Scientist - ML Capabilities

Pie Insurance (View all Jobs)

United States

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Interview Process

1. Phone screen with recruiter 2. Technical screen in the form of a pair-programming session to debug and test existing code 3. Final round is a multi-round session that typically includes demonstrations for backend, frontend, and design skills (and they are collaborative in nature) but are not odd Leetcode style questions. There is also a cultural/behavioral fit round, but that does not involve coding/design demonstrations.



Programming Languages Mentioned

SQL, Python

Pie's mission is to empower small businesses to thrive by making commercial insurance affordable and as easy as pie. We leverage technology to transform how small businesses buy and experience commercial insurance.
Like our small business customers, we are a diverse team of builders, dreamers, and entrepreneurs who are driven by core values and operating principles that guide every decision we make.
  • Your role will be pivotal in connecting complex data ecosystems and AI-ML models to solve real-world challenges. Collaborate with a dynamic team of Data Scientists and AI-ML experts in crafting and implementing AI-driven solutions that not only enhance our operational efficiencies but also set new benchmarks in industry innovation.
  • Dive into large, intricate datasets, and leverage your skills to make a significant, measurable impact in a field where your work will be seen and felt
  • Collaborate with platform and data engineering teams to ensure seamless integration and deployment of models into production systems

How You’ll Do It

  • Feature Engineering: Develop and maintain efficient data pipelines that source structured and unstructured data from various sources, ensuring feature integrity, availability, and optimization. Utilize NLP and generative AI capabilities to structure unstructured data to be used for ML model development. Collaborate with platform and data engineering teams to ensure seamless integration and deployment of models into production systems. 
  • Feature Discovery: Build tools and accelerators for feature construction and discovery, leveraging advanced ML and generative AI capabilities
  • Feature Foundry: In collaboration with MLOps and Data Engineering teams, design, prototype and implement feature repository with time-traveling capability. 
  • Accelerators: leverage open-source and proprietary techniques for building accelerators for AI-ML solution development and deployment
  • ML System Design: Work with Data Scientists and ML Engineers to gather requirements, architect, design, and help implement data-driven systems and platforms ensuring scalability, efficiency, and robustness. 
  • Leadership: Drive data-driven initiatives from conception to execution. Collaborate with cross-functional teams to ensure alignment, efficacy, and timeliness. 
  • Communication: Translate complex findings into understandable insights and present them to peers, leadership, and business stakeholders. 
  • Machine Learning: Develop and deploy unsupervised and supervised machine learning, and generative AI techniques to construct and validate predictive features from text, image, and structured data
  • Research & Development: Stay abreast of the latest developments in machine learning, and generative AI, incorporating new techniques and methodologies into our processes to keep us ahead in the insurance industry.

The Right Stuff

A Master’s Degree in Data Science, Computer Science, Statistics, Mathematics, or a related field and at least 7 years of relevant work experience or a Bachelor’s Degree in these fields with at least 9 years of relevant work experience.

  • 7+ years experience with and solid proficiency in a programming language such as Python and SQL
  • 4+ years experience with data orchestration workflow tools such as DBT, Airflow etc
  • 3+ years experience in building feature repository for training AI-ML models
  • 2+ years experience in data scraping 
  • 2+ years experience in processing text and image data using parallel processing technique
  • 4+ years experience working with public cloud ML capabilities, preferably AWS, Databricks, Docker, Kubernetes 
  • 2+ years experience in design and build of model-driven dashboarding and UI such as streamlit, Dash
  • Exposure to machine learning techniques and predictive modeling

Key Competencies

  • Creativity: Able to think outside the box to find innovative solutions to complex problems. 
  • Intellectual Curiosity: Passionate about learning and staying updated with the latest developments in the field.
  • Attention to Detail: Ensures precision and accuracy in all tasks and projects. 
  • Adaptability: Thrives in a fast-paced environment, adapting to changing business needs. 
  • Interpersonal Sensitivity: Works effectively in team settings, valuing and respecting the views and roles of others. 
  • Decision-Making: Makes sound decisions based on data, analysis, and experience. 
  • Strategic Thinking: Can envision long-term strategies and align day-to-day activities towards achieving them.


Base Compensation Range
$155,000$190,000 USD

Compensation & Benefits 

  • Competitive cash compensation
  • A piece of the pie (in the form of equity)
  • Comprehensive health plans
  • Generous PTO
  • Future focused 401k match
  • Generous parental and caregiver leave
  • Our core values are more than just a poster on the wall; they’re tangibly reflected in our work 

Our goal is to make all aspects of working with us as easy as pie. That includes our offer process. When we’ve identified a talented individual who we’d like to be a Pie-oneer , we work hard to present an equitable and fair offer. We look at the candidate’s knowledge, skills, and experience, along with their compensation expectations and align that with our company equity processes to determine our offer ranges. 

Each year Pie reviews company performance and may grant discretionary bonuses to eligible team members.

Location Information 

Unless otherwise specified, this role has the option to be hybrid or remote. Hybrid work locations provide team members with the flexibility of working partially from our Denver or DC office and from home. Remote team members must live and work in the United States* (*territories excluded), and have access to reliable, high-speed internet.

Additional Information

Pie Insurance is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military service status, citizenship, or other protected characteristic.

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Please mention No Whiteboard if you apply!
I'm a one-man team looking to improve tech interviews, and could use any support! 😄

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