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Data Instrumentation And Growth Measurement Lead Jobs

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Explore current data instrumentation and growth measurement lead jobs. Use filters to narrow by work mode, employment type, experience and date posted.

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Baseten
📍 San Francisco• Full-time• Remote
22 days ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE This is a sourcing-first role, not a deal-closing role. Baseten needs someone who can build and maintain deep relationships across the long tail of data center and powered land providers, well beyond the handful of large, well-known players that everyone in the market is already competing for. This coverage area is a key differentiator for Baseten's broader compute strategy, so we're looking for the best possible person in this specific lane rather than a generalist. You'll own the full lifecycle of a sourcing relationship — from first outreach to ongoing management — not just the introduction. WHAT YOU'LL DO Build and maintain a comprehensive map of data center and powered land opportunities, with a particular focus on the long tail rather than the handful of major, oversubscribed players Own the full sourcing lifecycle for each relationship — from identifying and reaching out to new providers, through negotiation support, to ongoing relationship management — not just the initial introduction Develop and manage sourcing relationships across neoclouds, hyperscalers, brokers, and independent operators Quickly and independently evaluate new sites and spaces to determine fit and priority Prepare business cases and cost analysis to support new data center and powered land opportunities, partnering with Finance where needed Maintain accurate records of suppliers, contracts, and commercial terms so the team has a reli

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Lyft
📍 Toronto• Full-time• From C$45/hr
23 days ago

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. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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Lyft
📍 Toronto• Full-time• From C$40/hr
23 days ago

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. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science or related major from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required) . For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for an internship in Toronto Strong knowledge of CS fundamentals Knowledge of SQL and data modeling fundamentals Experience working with databases Excellent communication skills Interest in solving large scale data problems in a real world scenario Passion for community, sustainability, and/or transportation Benefits: Mental health benefits In addition to holidays, interns receive 2 days paid time off and 3 days sick time off Subsidized commuter benefits and Lyft ride credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft belie

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Nextdoor
📍 Us Remote• Full-time• Remote• $190K – $283K/yr
1mo ago

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Data Scientist at Nextdoor, you will help design and oversee product experiments and own complex analyses to drive company and product strategy. We use a semi-embedded team structure, in which a group of data team members works on a specific product or pillar, interfacing directly with product and engineering stakeholders. The Data Science group consists of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, physics, statistics, and operations research. We are an integral part of the product development organization and play an active and collaborative role in building and improving the product. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You'll Make We are looking for a Staff Data Scientist to accelerate execution on priority content investments and elevate the quality of product decision-making.

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Baseten
📍 San Francisco• Full-time• Remote
1mo ago

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We’re hiring a Data Scientist to help build and scale our internal analytics capabilities. This is a foundational role where you’ll create dashboards, data models and insights to power business and product teams alike. You’ll collect requirements, define key metrics, and deliver insights directly to stakeholders. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape Baseten’s product and strategy. RESPONSIBILITIES Build and maintain production-grade dbt models and dashboards across multiple functions with a focus on accuracy, simplicity and user experience. Define and instrument core metrics around ROI, product adoption, customer lifecycle, capacity, availability, revenue and costs. Ingest and transform raw data using tools like dbt, Airbyte, and BigQuery. Partner with Engineering, Finance, Marketing, and Sales teams to understand goals and translate them into data solutions REQUIREMENTS 5+ years of experience in analytics engineering, data analysis, analytics, data science or a related role Advanced SQL and dbt skills, with a record of building models, tests, semantic layers and lineage in a cloud data warehouse. Prior experience supporting complex cross-functional projects across GTM, Finance and Engineering across various stages of the customer journey. Experience building dashboards and self-serve analy

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Pinterest
📍 San Francisco• Full-time• Remote• From $242.6K/yr
1mo ago

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a principal software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love. What you’ll do: Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling Work with internal customers on critical business use cases that rely on big data Provide thought leadership to the entire company on how data should be

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OpenAI
📍 San Francisco• Full-time
1mo ago

About the Team OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions. Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency. About the Role We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments. This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment. The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries. Key Responsibilities Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios. Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize

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Lyft
📍 Toronto• Full-time• From C$108K/yr
1mo ago

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 Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

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Plaid
📍 San Francisco• Full-time• Remote
1mo ago

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Senior Data Scientist - Network Value (Credit) The Network Value Data Science team is helping Plaid build an industry-leading fintech consumer network with best-in-class products and user experiences. We are a product analytics team embedded in key product areas across Plaid. We support some of Plaid’s most important OKRs and help execute on product roadmaps. We translate ambiguous product questions into tractable analysis, serve as analytical thought partners throughout the org, identify opportunities to build better products, and champion a data-first decision-making approach everywhere we go. You’ll be a Data Scientist supporting Credit, a critical product area within Plaid’s Network Value portfolio. You’ll become a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders, helping shape Credit product strategy, improve product performance and user experience, and grow Plaid’s consumer network. You’ll translate business questions into analytics projects, perform ad-hoc and strategic analysis, improve visibility into core systems through data modeling and dashboarding, create OKRs and KPIs tied to business goals and user experiences, a

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Lyft
📍 Toronto• Full-time• From C$108K/yr
1mo ago

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 Science 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 identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features. 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 a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare? What new airport product features can we introduce to grow rider demand? Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience? How can we optimize ride offerings for each rider to maximize conversion? Responsibilities Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Desi

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Baxter
📍 Bengaluru
1mo ago

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Perform development work and technical support related to our data transformation and ETL jobs in support of a global data warehouse. Can communicate results with internal customers. Requires the ability to work independently, as well as in cooperation with a variety of customers and other technical professionals. What you'll be doing Development of new ETL/data transformation jobs, using PySpark and IBM DataStage in AWS. Enhancement and support on existing ETL/data transformation jobs. Can explain technical solutions and resolutions with internal customers and communicate feedback to the ETL team. Perform technical code reviews for peers moving code into production. Perform and review integration testing before production migrations. Provide high level of technical support, and perform root cause analysis for problems experienced within area of

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We are looking for an experienced Senior Manager - Data Loss Prevention (DLP) - to join us! As a Senior Manager, you will work as a part of our Cyber Security team, and you will collaborate with other IT professionals to ensure that sensitive data is protected from unauthorized access misuse, and breaches. Your role will also cover Data Security Posture Management (DSPM), disk encryption controls, discovery and classification technologies, and Database Activity Monitoring (DAM) solutions. Source: Adani Group | Job ID: 57062

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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Notion
📍 San Francisco• Full-time
1mo ago

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About The Role: You will apply your expertise in statistical inference and experimentation to understand the impact of product changes and drive decision-making. You will explore ambiguous areas and conduct analysis to identify opportunities for the Growth org, helping shape the strategy and roadmap. You'll partner closely with product, engineering, and marketing leaders at every step of the development process, driving forward data science and analytics work. You'll work with your teams to determine north star and operational metrics, and build the foundational datasets and dashboards to monitor progress and make key decisions. You'll influence the broader company by communicating your findings and driving change in our product and business. (Insights are useful. Impact is even better!) Skills You'll Need to Bring: You are comfortable with ambiguity and motivated by business results. You have expertise in SQL and at least one scripting language (ideally Python or R). You know how to use statistical inference and experimentation to drive actionable recommendations. You are comfortable transforming raw data to build your own data sets

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