At a Glance
- Tasks: Lead the development of advanced Customer Lifetime Value models for our unique two-sided platform.
- Company: Join Bumble Inc., a pioneer in fostering kind connections through innovative tech.
- Benefits: Inclusive workplace, flexible working options, and opportunities for professional growth.
- Other info: Collaborative culture that values diverse perspectives and encourages personal growth.
- Why this job: Make a real impact on customer insights and revenue strategies in a fast-paced environment.
- Qualifications: Graduate degree preferred; experience in data science and machine learning essential.
The predicted salary is between 60000 - 80000 £ per year.
Bumble Inc. is seeking a Senior Data Scientist to lead our efforts in developing sophisticated Customer Lifetime Value (CLV) models tailored specifically for our unique ecosystem. This is a unique opportunity for an experienced MLE/DS who enjoys the fast-paced environment of a growing company, has experience in tech analytics and has a passion to contribute to helping the Bumble Inc. mission to foster kind connections.
You would ideally have a background in data science at either a dating, social, gaming or other relevant tech company, with proven experience in driving commercial impact through applying analytics to critical business problems.
In this role, you will collaborate closely with cross-functional teams to harness the power of data and analytics in unlocking key insights into customer behavior and revenue generation. Your primary focus will be on developing advanced CLV models that account for the intricacies of our two-sided marketplace, enabling us to optimize customer acquisition, retention, and monetization strategies.
You bring experience of working with complex sources of revenue, payments and behavioural data and use that knowledge to partner with stakeholders and senior leaders, taking a holistic approach to find answers. You are comfortable challenging priorities and clearly communicating analytical roadmaps. You’re able to effectively balance demands for both tactical and strategic work and also have experience managing projects across analytics engineering, data science and MLOps.
KEY ACCOUNTABILITIES- Lead the development of advanced CLV models tailored to the unique dynamics of our two-sided marketplace, leveraging complex sources of revenue, payments, and behavioral data.
- Collaborate closely with stakeholders and senior leaders to identify key business problems, challenge priorities, and provide actionable insights derived from CLV modeling.
- Guide others on techniques and ways of working and help build a culture of critical thinking, commercial acumen and disciplined execution in alignment with senior management.
- Drive data science roadmaps by efficiently producing insights that inform decision-making, supporting an extensive experimentation program, and advocating for continual improvement within the team.
- Take an integrated perspective to analytics, considering all potential drivers to a problem, reviewing existing knowledge, and leveraging expertise from other teams to enhance the effectiveness of CLV modeling efforts.
- Preference for a graduate degree in Mathematics, Engineering, Information Sciences, Economics, Finance, or STEM. PhD and Masters welcome.
- Preference for experience working in similar dating/social/gaming tech product industries or else financial services/high-data-volume industries.
- Proven experience in building and deploying ML and statistical models for demand forecasting, segmentation, and CLV estimation.
- 3+ years of experience with python/SQL, machine learning/data science tooling such as Kubeflow/Streamlit and visualisation tooling such as Looker/Tableau.
- You have strong understanding of machine learning applications development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring and alerting.
- You have experience working with complex data infrastructures and have experience partnering and guiding the work of data engineering to help facilitate ingestion, warehousing, and optimisation of databases.
- Strong experience with data engineering and data modelling requirements needed to automate reporting and measurement.
Senior Data Scientist, Revenue & CLV for Two-Sided Platform employer: Bumble
Bumble Inc. is an exceptional employer that champions diversity and inclusion, creating a supportive work environment where every voice is valued. As a Senior Data Scientist, you'll thrive in a dynamic culture that encourages innovation and collaboration, with ample opportunities for professional growth and development. Located in a vibrant tech hub, Bumble offers unique advantages such as flexible working arrangements and a commitment to fostering kind connections, making it a truly rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist, Revenue & CLV for Two-Sided Platform
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Bumble Inc. on LinkedIn. A friendly chat can give us insider info about the company culture and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your data science skills. Be ready to discuss your experience with CLV models and how you've tackled complex data problems in the past. We want to see your passion shine through!
✨Tip Number 3
Showcase your collaborative spirit! Bumble values teamwork, so think of examples where you’ve worked with cross-functional teams. Highlight how you’ve driven insights that made a real impact.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Senior Data Scientist, Revenue & CLV for Two-Sided Platform
Some tips for your application 🫡
Show Your Passion:When writing your application, let us see your enthusiasm for data science and how it aligns with Bumble's mission. Share specific examples of how you've used analytics to drive impact in previous roles, especially in tech or similar industries.
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight relevant experience with CLV models, machine learning, and any work with complex data sources. We want to see how your skills fit into our unique two-sided marketplace!
Be Authentic:Don’t shy away from sharing your pronouns and any adjustments you might need during the process. We value authenticity and want to create a comfortable environment for everyone applying, so just be yourself!
Apply Through Our Website:For the best chance of success, make sure to apply through our website. This way, we can easily track your application and ensure it gets the attention it deserves. Plus, it’s super straightforward!
How to prepare for a job interview at Bumble
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around Customer Lifetime Value (CLV) models. Be ready to discuss your experience with machine learning and statistical models, as well as how you've applied these in real-world scenarios, particularly in tech or high-data-volume industries.
✨Show Off Your Collaboration Skills
Since this role involves working closely with cross-functional teams, prepare examples of how you've successfully collaborated with stakeholders and senior leaders in the past. Highlight any instances where you challenged priorities or provided actionable insights that drove business decisions.
✨Be Ready to Discuss Complex Data
Familiarise yourself with the intricacies of working with complex sources of revenue, payments, and behavioural data. Be prepared to explain how you've tackled similar challenges before and how you can leverage that experience to optimise customer acquisition and retention strategies.
✨Communicate Clearly and Confidently
Practice articulating your analytical roadmaps and insights clearly. This role requires balancing tactical and strategic work, so be ready to discuss how you manage projects across analytics engineering, data science, and MLOps while keeping communication open and effective.
