Senior Data Scientist, Consumer Apps

We need to output HTML fragment with sections: About the role? Actually the posting includes description. We need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to include sections only when posting has real specific content. We must not repeat job title. No Job ID. Remove boilerplate like EEO, etc. We need to preserve substantive info. Let's parse content: First paragraph: description of Roblox mission etc. Could be "About the role" or maybe "About the team". The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can decide which sections are appropriate. We have: - Why Data Science & Analytics? (mission) - Why Consumer Apps? (team description) - As a Data Scientist on the team, you will ... (responsibilities) - You Will (list of responsibilities) - You Have (requirements/qualifications) - For roles based at HQ: pay range, schedule info. - Benefits: mention equity compensation and benefits as described on this page (but not detailed). We cannot create Benefits section unless posting actually states them. It says "All full-time employees are also eligible for equity compensation and for benefits as described on this page." That's a statement about benefits but not specific. Might be considered vague; but it's still a statement that benefits exist. However instruction: never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. It does state benefits exist (eligible for equity compensation and benefits). That's not placeholder; it's a statement. So we could include Benefits section with that sentence. Pay: they give Annual Salary Range $263,670—$322,820 USD. That's specific. So Pay section. Schedule: "Roles that are based in an office are onsite Tuesday, Wednesday, Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted)." That's specific schedule. So Schedule section. We also have "For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below." So Pay section applies to HQ roles. We'll include Pay. We need to avoid duplication. Also need to remove EEO boilerplate etc. We need to preserve all substantive info: mission statements, responsibilities list, qualifications, etc. Let's extract sections: About the role? Could combine the introductory paragraphs about Roblox mission and why Data Science & Analytics and why Consumer Apps. That could be "About the role" or maybe "About the team". We'll use "About the role". Provide prose. Responsibilities: The bullet list starting with "As a Data Scientist on the team, you will help accelerate..." and then the "You Will" list. We'll combine into responsibilities. Requirements/Qualifications/Skills: The "You Have" list includes advanced degree, 8+ years experience, strong analytical skills, proficiency in Python/R, SQL, Spark, Airflow, deep expertise in statistical analysis, causal inference, experimentation, measurement methodologies, ability to lead ambiguous high-impact problem spaces, influence across teams, communication skills. Could be split into Qualifications and Skills. But we can combine into Requirements. However instruction: prefer few substantive sections over many thin ones. So maybe we have one "Requirements" section covering all. But we also have "Skills" maybe separate. However we can keep one Requirements. We need to use

• for any list of duties/requirements/benefits. So responsibilities list as
  . Requirements list as
  . Benefits list as
  (though only one item maybe). Pay and Schedule as

  . Let's craft. First, About the role: combine paragraphs: "Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone." Then maybe add "WHY DATA SCIENCE & ANALYTICS?" and "WHY Consumer Apps?" as part of About the role. Could incorporate. We'll include those as prose. Now Responsibilities: start with "As a Data Scientist on the team, you will help accelerate Roblox’s growth by shaping how we launch and optimize Roblox across the diverse device ecosystems where people connect, play, and co-experience." Then bullet list from "You Will". Let's extract each bullet: - Identify high-potential platform levers and apply causal methods to understand their impact on user behavior, engagement, monetization, and other topline outcomes, translating these insights into platform-specific strategies. - Develop deep expertise in the unique dynamics of each platform — including how the product is experienced, how user cohorts differ, and what drives their behavior — and proactively bring this perspective to broader research and cross-functional decision-making to identify opportunities and explain differences in product and business outcomes. - Build visibility into platform-level business performance and establish growth targets informed by internal data, market research, and competitive insights. - Design and analyze experiments to evaluate product launches, inform iteration, and drive rigorous, data-informed product decisions. - Advance how we measure product impact by developing innovative measurement and causal inference approaches where traditional A/B testing is not feasible, expanding the range of platform investments we can evaluate with rigor and confidence. - Elevate data and experimentation rigor across the broader team by building scalable frameworks and practices around experiment design, success metrics, launch criteria, and launch readiness — helping teams launch confidently and consistently. - Build scalable monitoring and diagnostic capabilities that enable teams to quickly identify trends, investigate changes, and understand root causes. - Partner across Data Science, Product, and Engineering — including Growth, Discovery, Social, and other product areas — to connect insights across surfaces, understand how platform and product changes affect the broader ecosystem, and translate complex data into actionable recommendations that shape strategy and drive impactful platform improvements. We'll put each as

  • . Now Requirements: from "You Have". Let's list: - An advanced degree in Statistics, Applied Mathematics, Physics, Engineering, Computer Science, Economics, or a related quantitative field. - 8+ years of industry experience in Data Science or a related quantitative discipline, preferably working on consumer-facing products or applications. - Strong analytical and technical skills, with proficiency in Python or R, SQL, and large-scale data processing and workflow tools such as Spark and Airflow. - Deep expertise in statistical analysis, causal inference, experimentation, and measurement methodologies, with a track record of applying these techniques to shape product strategy and drive business outcomes. - Demonstrated ability to independently lead ambiguous, high-impact problem spaces, applying first-principles thinking to develop novel frameworks, approaches, and solutions. - Proven ability to influence across Product, Engineering, Design, Data Science, and leadership, shaping strategy, prioritizing investments, and driving alignment across organizational boundaries. - Exceptional communication and storytelling skills, with the ability to distill complex, high-dimensional problems into clear insights and actionable recommendations for both technical and executive audiences. We'll put as
    . Benefits: "All full-time employees are also eligible for equity compensation and for benefits as described on this page." Could be a single
    • or

      . Since it's a list of benefits (though not detailed), we can make a

      • Eligible for equity compensation and benefits as described on the company benefits page.
      . That's acceptable. Pay: "Annual Salary Range $263,670—$322,820 USD". Also note that actual base pay dependent on factors etc. We'll include that as

      . Might also include note about equity compensation already in Benefits. Schedule: "Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted)." We'll put as

      . We must not include boilerplate like EEO, visa, etc. Remove those paragraphs. Now produce HTML fragment: no or . Just sections. We'll order: About the role (

      About the role

      ...)

      , Responsibilities (

      Responsibilities

      ...), Requirements (

      Requirements

      ...), Benefits (

      Benefits

      ...), Pay (

      Pay

      ...), Schedule (

      Schedule

      ...). Check that we don't repeat job title. Good. Now ensure we preserve all substantive info: we included mission, why DS&A, why Consumer Apps, responsibilities list, qualifications, benefits, pay, schedule. Did we miss any? The "Why Data Science & Analytics?" paragraph: "The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact on our community of players and developers." We should include that in About the role. Also "WHY Consumer Apps?" paragraph: "Roblox is used by tens of millions of people every day across a wide range of devices, including mobile, desktop, console, TV, and VR. The Consumer Apps team owns the app foundation that makes Roblox feel fast, fluid, and reliable for players and is dedicated to delivering superior performance, reliability, and user experience across all platforms Roblox supports. This team ensures a seamless and engaging user interface that facilitates intuitive interactions while enabling efficient, high-quality experiences across devices. Innovation is at the core of our work, as we continuously enhance features and integrate cutting-edge technologies to solve complex problems." Include. Thus About the role will be a combination of those paragraphs plus the initial mission. Let's craft About the role paragraph(s). Could be multiple

      under the heading? The instruction: use

      for prose. So we can have multiple

      elements under the heading. We'll do:

      About the role

      Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

      WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning.