Okay, I've searched for Data Scientist roles in Boston, MA within the tech industry, requiring 1-3 years of experience, with skills in Python and SQL, for full-time positions. I have found 124 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Data Scientist role at Jerry is fundamentally about leveraging data to drive and accelerate the company's ambitious growth as it scales from 5 million to 50 million customers and pursues a $10 billion valuation. More than just a technical analyst, the candidate will be a strategic partner working closely with business operations, marketing, and product teams to translate complex data into actionable insights, especially around user acquisition, partnerships, and automation. The emphasis on advanced machine learning models and experimentation (A/B testing) highlights a need for rigor and innovation to optimize growth levers in a fast-moving startup environment. The preferred background in management consulting or business analysis reflects the expectation for structured problem-solving, critical thinking, and clear communication—skills vital to influencing diverse stakeholders from frontline staff to executives. Success in this role means not only mastering technical proficiencies like Python and SQL but also embodying a mindset of continuous excellence and first-principles thinking to identify and solve scalable, impactful problems, often under ambiguity and rapid change. The candidate must be autonomous yet collaborative, comfortable navigating cross-functional dynamics, and able to push the data-driven agenda to inform high-stakes decisions in a high-growth, competitive market.

Company Analysis:

Jerry occupies a highly disruptive and rapidly growing position in the automotive tech and insurtech market, aiming to be the first and only AllCar™ super app that simplifies every facet of car ownership through AI-driven innovation. Positioned as a well-funded, pre-IPO startup with exponential revenue and customer growth, Jerry combines fintech, insurtech, and automotive expertise to redefine how millions of Americans manage a traditionally cumbersome experience. The culture likely values speed, relentless innovation, and a customer-first mindset, demonstrated by their seamless all-in-one app and emphasis on removing friction from car ownership. For a data scientist, this means working in a dynamic, talent-dense environment with strong leadership vision and a growth-oriented mandate. The connection to a Director of BizOps & Analytics signals close alignment with core business strategy and high visibility within the company. Roles here are expected to be both hands-on and strategic, requiring agility and strong communication skills to influence internal partners in a non-hierarchical but goal-driven culture. Being at a pivotal moment—post-profitability with plans for massive scaling—this role is clearly a strategic hire critical to sustaining rapid growth, enhancing operational efficiencies, and helping Jerry cement its market leadership and expansive product vision.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to use data to influence a cross-functional team with varying levels of technical understanding. How did you approach the communication?
• Behavioral: Describe a challenging problem you solved using first principles thinking. What was your process and what was the outcome?
• Behavioral: Can you share an example when you led or contributed to an A/B testing experiment? What were the challenges and how did the results impact the business?
• Behavioral: How do you maintain high standards and push your team or peers towards excellence in your work?
• Technical: Walk me through how you would design and implement a machine learning model to predict user acquisition success across different marketing channels.
• Technical: How would you approach automating a manual data reporting process in a fast-paced startup environment? Which tools and metrics would you prioritize?
• Technical: What experience do you have with SQL and Python in the context of business analytics and experimentation? Can you provide an example of a complex query or script you've built?
• Technical: Explain how you would interpret results from an A/B test where key metrics show conflicting signals. How do you decide the next steps?
• Situational: Imagine our marketing team launches a new partnership campaign but the performance falls below expectations. How would you analyze the situation and recommend actions?
• Situational: You uncover a data anomaly suggesting possible user churn in a key segment, but the product team disagrees. How do you navigate this disagreement?
• Situational: If given limited data quality or incomplete datasets, how would you still deliver meaningful insights for growth strategies?
• Company Fit/Motivation: What attracts you specifically to Jerry.ai and its mission to reinvent car ownership through AI?
• Company Fit/Motivation: How do you see your problem-solving philosophy and work style aligning with a fast-moving, innovation-driven startup culture?
• Company Fit/Motivation: Jerry emphasizes a customer-first mindset combined with cutting-edge AI; how would you ensure your data work reflects these values?
• Candidate Questions: How does the data science team at Jerry interact with other departments, and what does successful cross-functional collaboration look like here?
• Candidate Questions: What are the biggest challenges Jerry anticipates in scaling from 5 million to 50 million customers, and how can this role contribute most effectively?
• Candidate Questions: How does Jerry’s leadership envision the role of data science evolving post-IPO and in driving future product innovation?