Data Scientist (User Growth) - job 1 of 7

As a Data Scientist (User Growth) at Jerry, your primary responsibilities include defining and analyzing the levers that drive user acquisition across various channels, designing and executing A/B tests, building reports, and predictive models. You'll work closely with marketing and product teams to translate insights into strategic decisions that will significantly increase our user base.

To qualify for the Data Scientist (User Growth) position at Jerry, applicants should have a Bachelor's degree in a quantitatively rigorous discipline, with at least 3 years of experience in consulting, data science, or growth analytics. Proficiency in SQL and Python or similar programming languages is essential, as well as strong problem-solving skills and the ability to communicate effectively with various stakeholders.

A Data Scientist (User Growth) at Jerry will work on projects focused on understanding user acquisition dynamics, running analytical experiments, and building models to optimize marketing efforts. You'll be instrumental in identifying profitable channels and informing growth decisions that align with the company's wider business goals.

In the role of Data Scientist (User Growth) at Jerry, you will directly contribute to the company's growth by driving insights that will enable the team to make data-driven decisions on marketing investments and user acquisition strategies. Your work will be essential in scaling our user base from 5M to 50M.

At Jerry, a Data Scientist (User Growth) can anticipate a collaborative team environment filled with highly skilled individuals from various backgrounds. The company's culture encourages innovation, creativity, and open communication—making it an excellent place for someone looking to grow and share ideas.

When answering this question, highlight specific projects where you implemented A/B tests, detailing your approach to designing the test, the metrics you used to measure success, and the outcomes. Think of a challenge you faced during the process and how you overcame it while emphasizing the importance of testing in driving growth decisions.

In your response, share your methodology for building predictive models, including data collection, selection of algorithms, and model validation techniques. Illustrate your experience by referencing a specific model you've created, the insights generated, and its impact on growth strategies.

Use this question to showcase your ability to simplify complex data. Explain how you tailored your presentation, the techniques you used to make the insights accessible, and how the information led to actionable decisions by the stakeholders. Include any feedback you received to illustrate the effectiveness of your communication.

Discuss the data analysis tools you are proficient with, such as SQL, Python, R, or visualization tools like Tableau or Power BI. Provide examples of how you’ve utilized these tools in previous roles to derive valuable insights and inform decision-making, highlighting your adaptability to new technologies.

Explain the processes you follow to validate data, including cleaning techniques, consistency checks, and cross-verifying data sources. Mention any tools or frameworks you've used to facilitate this process and speak about the importance of data integrity in your past projects.

In your response, talk about metrics you consider critical for evaluating user acquisition efficiency, such as customer acquisition cost (CAC), lifetime value (LTV), and conversion rates. Describe an instance where you analyzed such metrics, the insights you derived, and how they influenced marketing strategies.

Emphasize the importance of teamwork in your work. Share experiences where collaborating with cross-functional teams led to improved outcomes, highlighting how shared insights from various departments can enhance data-driven decision-making.

Discuss your strategies for professional development, such as following relevant online resources, attending conferences, or participating in webinars. You might also mention how you implement new findings or techniques in your work to drive innovation at Jerry.

Detail your experience with machine learning algorithms, including projects where you've applied them. Discuss specific algorithms you've worked with, the problems they addressed, and any frameworks or libraries that were crucial to your work, demonstrating how this knowledge can contribute to Jerry’s growth initiatives.

This is your chance to show genuine interest in Jerry and its mission. Explain what specifically attracts you to this role and company, mentioning its innovative approach and impressive growth. Make sure to connect your career goals with the opportunities this position presents.