At a Glance
- Tasks: Lead a team of data scientists to drive product strategy and analytics for Meta's Shops Ads.
- Company: Join Meta, a leader in tech innovation and analytics.
- Benefits: Competitive salary, career growth, and a vibrant analytics community.
- Other info: Dynamic role with opportunities to mentor and advance data science practices.
- Why this job: Make an impact with one of the largest data sets while shaping product direction.
- Qualifications: 4+ years in analytics, team management, and proficiency in SQL and Python.
The predicted salary is between 80000 - 100000 £ per year.
You will apply your people leadership, project management, analytical, and technical skills, creativity, and product intuition to one of the largest data sets in the world. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will influence product strategy and investment decisions with data, be focused on impact, and lead and grow a high-performing team. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
About the role:
- Product leadership: You will use data to understand the product and business ecosystem, quantify new opportunities, identify upcoming challenges, and shape product development to bring value to people, businesses, and Meta. You will help develop strategy and support leadership in prioritising what to build and setting goals for execution.
- Analytics: You will guide Ads product teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
- Communication and influence: You won’t simply present data, but tell data-driven stories. You will convince and influence leaders using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
- People leadership: You will inspire, lead and grow a world-class team of data scientists and data science leaders.
Responsibilities
- Lead a team of Data Scientists to develop strategies for Meta's Shops Ads products that serve hundreds of millions of people, businesses, and partners around the world.
- Drive analytics projects end-to-end as part of a cross-function team across Product, Engineering, and Analytics. These projects will be used to drive product strategy, influence investment decisions, and support efficient execution.
- Leverage analytics and product insights to influence senior leadership and drive product direction.
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
- Identify and measure success of ads product efforts through goal setting, measurements, and understanding of key product metrics to inform product team direction.
- Discover, define, understand, and test different levers for driving product improvements, utilising these insights to steer the direction taken in product.
- Contribute towards the advancement of Data Science as a discipline at Meta, including but not limited to driving data best practices, improving analytical techniques, scaling knowledge, and mentoring other Data Scientists.
Minimum Qualifications
- A minimum of 4 years of work experience (2+ years with a Ph.D.) in applied analytics, including a minimum of 2 years of experience managing analytics teams.
- Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).
Preferred Qualifications
- Bachelor degree or equivalent in Mathematics, Statistics, Computer Science, Engineering, Economics, or another quantitative field.
- Master’s or Ph.D. degree in Mathematics, Statistics, Computer Science, Engineering, Economics, or another quantitative field.
- Proven track record of leading high-performing analytics teams.
- Experience initiating and completing analytical projects with minimal guidance.
- Experience communicating results of analysis to senior leadership.
Data Science Manager, Monetisation employer: Meta Platforms, Inc.
Meta is an exceptional employer that fosters a dynamic and inclusive work culture, where innovation thrives and employees are empowered to lead impactful projects. With a strong focus on professional development, you will have access to a world-class analytics community dedicated to enhancing your skills and advancing your career. Located in a vibrant environment, Meta offers unique opportunities to collaborate with diverse teams and influence product strategies that reach millions globally.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager, Monetisation
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even casual coffee chats. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t just talk about your experience—show them! Bring along a portfolio of your projects or case studies that highlight your analytical skills and creativity.
✨Tailor Your Approach
Every company is different, so make sure you tailor your conversations to fit their culture and values. Research their products and challenges, and come prepared with ideas on how you can contribute to their success.
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Meta.
We think you need these skills to ace Data Science Manager, Monetisation
Some tips for your application 🫡
Show Your Analytical Skills:Make sure to highlight your experience with data querying languages and analytical projects. We want to see how you've used data to drive decisions and influence product strategy in your previous roles.
Tell a Data-Driven Story:When you write your application, don’t just present facts. We love a good narrative! Use your communication skills to weave a compelling story around your data insights and how they’ve impacted business outcomes.
Highlight Leadership Experience:Since this role involves leading a team, it’s crucial to showcase your people leadership skills. Share examples of how you've inspired and grown teams in the past, and how you plan to do the same with us at StudySmarter.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our community!
How to prepare for a job interview at Meta Platforms, Inc.
✨Know Your Data Inside Out
As a Data Science Manager, you'll be working with massive datasets. Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've used data to drive product strategy or influence decisions.
✨Tell a Compelling Story
You won't just present data; you'll need to tell a story with it. Prepare examples of how you've communicated complex insights to senior leadership in a clear and impactful way. Think about how you can showcase your ability to influence and inspire through data-driven narratives.
✨Showcase Your Leadership Style
Since you'll be leading a team, it's crucial to convey your people leadership skills. Prepare to discuss your approach to mentoring and developing talent within your team. Share specific instances where you've inspired your team to achieve high performance.
✨Be Ready for Cross-Functional Collaboration
You'll be collaborating with various teams, so highlight your experience working across different functions like Product, Engineering, and Marketing. Think of examples where you've successfully driven analytics projects in a cross-functional setting and how you navigated challenges along the way.
