Lead Analytics Engineer

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Staff Product Analyst, Product Analytics San Mateo, Los Angeles, or San Diego, United States This role will serve as a strategic analytics lead across multiple product and business areas, partnering closely with Product, Engineering, Data Science, Analytics Engineering, Finance, and other cross-functional teams. The Staff Product Analyst will be responsible for identifying long-term monetization and product growth opportunities, shaping product strategy through data-driven insights, and establishing scalable measurement frameworks that support decision-making across initiatives. Responsibilities Serve as a strategic analytics thought partner , using data to shape product strategy, challenge assumptions, identify opportunities and risks, and influence key decisions. Lead analytics strategy for complex product areas , partnering with Product, Engineering, Business, and Data teams to translate strategic objectives into KPIs, targets, measurement frameworks, and actionable insights. Lead measurement and experimentation strategy , including A/B testing and causal inference approaches, ensuring rigorous methodologies are applied to evaluate product impact and inform investment and launch decisions. Own complex, ambiguous analytics initiatives end to end , defining the a

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.” As a Data Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward. Responsibilities Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals Develop frameworks and scalable processes to drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience Monitor and diagnose KPI performance and present findings to senior leadership Experience Degree in a quantitative field like statisti

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of product changes. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As an Analytics Lead on the Airport team, you will collaborate with our team of engineers, product managers, and designers to conduct thorough data deep dives on airport performance, challenge our current strategy, and recommend enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: How should we determine pricing and earnings for airport rides? Who are our current airport drivers and what segment can we focus on to grow our supply? How does this strategy interact with driver bonuses? Which airports are underperforming and which key metrics can we use to identify and classify airport performance? What targets should we set for these key metrics and how do we efficiently monitor these metrics? What is driving high cancellation rates today and which types of riders/drivers are cancelling? What product changes can we implement to reduce cancellation rates? How are riders and drivers using different ride modes at airports, and how do we design

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Fulfillment group, in Marketplace, at Lyft is responsible for determining what inventory can be reliably offered for a given rider session and reliably fulfilling rider requests. The group has a few sub teams that are responsible for generating feasible offers for riders, connecting rider requests with drivers to fulfill those offers and a demand and supply lifecycle platform that power great rideshare experience. As a software engineer at Lyft, you'll collaborate with other software engineers and cross functions like product, data science and analytics to lead and execute large projects from idea to efficient execution. We're looking for a motivated Software Engineer who is passionate about solving challenging technical problems and is excited about working in a fast-paced, innovative and cross-functional environment where they will take on some of the most interesting and impactful problems in ridesharing. Responsibilities: Contribute to the roadmap and architecture based on technology and business needs Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various trade offs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Build Features from tech specification to positive execution Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags and tech talks Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or relevant work experience 3+ years of software engineering industry experience Proficiency in object-oriented programming Experience designing, debugging and running fault-tolerant, highly available, large-scale di

Analytical Engineering Manager The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call. As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questions without routing through your team. This role is based in our Vancouver office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and t he teams with which you partner . If you're interviewing for this role, your recruiter will shar e more about the in-office requirements . What you’ll achieve Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, and set a high bar for data-model quality and stakeholder trust. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM): Your team is accountable for the curated data models, canonical metrics, dashboards, and Genie spaces the business depends on. Treat every recurring insight as a product with an owner, a cadence, and an SLA: Build a catalog of trusted, versioned data products instead of one-off rebuilds. Drive self-serve enablement: Prioritize the Gold tables, governed metric definitions, and metadata that make Claude + Databric

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han