Data Scientist, Enterprise

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role: We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we need people who are obsessed with understanding how users experience our product and can turn that understanding into decisions that move the needle. You'll directly impact Replit's growth by turning user behavior into actionable insights that shape product strategy, improve activation and retention, and drive sustainable revenue growth across our self-serve and enterprise segments. Who You are You're a data scientist who moves fast and goes deep. You can spin up an analysis in hours that would take others days; not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You're the person who digs past the top-line number to find the confound, questions whether the metric actually measures what people think it does, and pressure-tests your own work before anyone else sees it. You treat experimentation as a craft, not a checkbox. You've felt the pain of underpowered tests and novelty effects, and you have the judgment to get it right. You use AI agents and tools aggressively to multiply your output - writing code, exploring data, generating hypotheses, but you treat every AI-assisted output as a draft, not a deliverable. You know what good analysis looks like and you won't ship anything that doesn't meet that bar. The result is that you operate at a speed and depth that most DS teams can't match. You will: Design and analyze product experiments to evaluate feature launches, onboarding changes, and in-product interventions with rigorous statistical

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role You'll be one of the founding data scientist on Replit's Growth team, working with Product and Engineering leadership across acquisition, activation and recommender systems, and helping shape how Replit experiments. This role is for someone who doesn't wait to be asked. You spot problems and opportunities before anyone else does, bring a strong point of view, and push it until it changes what we build. You will: Own data science for major growth areas, partnering with PMs and engineers from problem framing and sizing through launch and readout Make fast decisions trustworthy: we ship weekly and need a decision within days, but retention takes weeks to show up. You'll design the experiments and metrics that close that gap; for example, variance reduction (CUPED), sequential testing, and short-term proxy metrics validated against long-term retention and revenue Help set the experimentation standards teams rely on for Replit's highest-traffic surfaces: how metrics and guardrails are defined, and the checks that catch a broken test before it misleads anyone Use quasi-experimental designs (difference-in-differences, synthetic control, regression discontinuity) where randomization isn't feasible, such as pricing changes and regional launches Help define the data science behind an emerging personalization and recommendations workstream: problem framing, offline and online evaluation, and measuring incremental lift Model the economics of a freemium, usage-based product: credit consumption, conversion, and how pricing and limits change behavior Develop user and project segmentation from behavioral and content signals (e.g., embeddings and clustering) so growth analysis reflects what people are actually building P

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. Realizing that vision requires a platform that legitimate users can trust and adversarial actors cannot exploit. We're hiring a Data Scientist to help build Replit's Trust & Safety and Anti-Abuse program from the ground up. You'll turn noisy behavioral, identity, payment, infrastructure, and content signals into the measurement systems, detections, and decisions that protect Replit's users, platform, and economics. You'll work closely with Engineering, Support, Legal, Security, Infrastructure, Money, and Growth to make abuse economically unviable while keeping friction low for legitimate users. Replit sits at the frontier of AI-native abuse. Our platform is a target for phishing and scam hosting, cryptomining, LLM token farming, card and coupon fraud, referral abuse, and increasingly, abuse driven by AI agents themselves. You'll help define how we identify, measure, and respond to these threats without compromising the experience of good users. Who You Are You're a data scientist who moves fast, goes deep, and thinks adversarially. You can spin up an analysis in hours that would take others days, not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You dig past the top-line abuse rate to understand selection effects, missing labels, policy changes, attacker adaptation, and the false positives hidden inside an aggregate metric. You understand that Trust & Safety data is imperfect and outcomes are high stakes. Ground truth is delayed, biased, and often incomple

Zoox is on an ambitious journey to develop a full-stack autonomous vehicle system for cities. We are seeking a Senior Data Scientist to join a verification and validation team that evaluates safety-critical AI systems. You will join a team of software and data engineers that leverage methods including log data analysis, simulation, and closed-course structured testing. You'll work cross-functionally with AI software, System Design and Mission Assurance, Simulation, Sensors, and other teams to develop, execute, and iterate on validation methods and pipelines. These pipelines evaluate safety-critical systems, are highly visible, and are an important critical path element of launching our service. The ideal candidate brings a hybrid of statistical rigor and engineering mindset to drive clarity from ambiguity, establish new processes, and propel the team forward. This is a deeply technical and hands-on role where you will be expected to be a self-sufficient builder and coder, not just a manager of projects. In this role, you will: Design Evaluation Frameworks: Architect statistical methodologies for safety-critical AI systems to form objective, rigorous conclusions about their performance and reliability. Conduct Robust Analysis: Deliver validation evidence to support increasingly complex operations and identify potential edge-case failures. Inform Strategy: Deliver clear, data-driven insights to development teams to guide system improvement, and to executive leadership to inform milestone-level go/no-go decisions. Define Metrics: Drive alignment across engineering teams on performance metrics and data extraction strategies. Lead the Lifecycle: Manage all phases of evaluation including prototyping, requirements capture, design, implementation, and validation. Scale Pipelines

We are seeking a highly skilled and experienced Staff Data Scientist to join our team and play a pivotal role in developing and deploying cutting-edge autonomous driving technologies. As a Staff Data Scientist, you will be responsible for tackling complex data challenges, driving innovation in machine learning and statistical modeling, and contributing to the advancement of our self-driving systems. You will work closely with a team of talented engineers and researchers in a fast-paced, collaborative environment. In this role, you will: Analyze large-scale datasets from various sources, such as fleet and simulation data, to extract actionable insights. Develop and evaluate novel algorithms and methodologies for data processing, feature engineering, model training, and performance optimization. Evaluate and validate model performance through rigorous testing and analysis, ensuring the safety and reliability of our systems. Communicate complex technical findings and recommendations to both technical and non-technical audiences. Mentor and provide technical guidance to junior data scientists and engineers. Qualifications Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with 8+ years of experience as a Data Scientist. Strong programming skills in Python, including experience with relevant libraries such as scikit-learn, and Pandas & SQL. Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling. Experience working with large-scale datasets and distributed computing platforms (e.g., Spark, Hadoop) with solid understanding of data processing, feature engineering, and data visualization techniques. Strong communication and presentation skills, with the ability to effectively convey technical information to diverse audiences. Bonus Qualifications Experienc

About Zoox Zoox is an autonomous ridehailing company building the world's first purpose-built robotaxi — fully electric, bidirectional, with no steering wheel or driver's seat. Backed by Amazon and founded to make transportation safer, cleaner, and more accessible, Zoox designs its vehicles entirely around the rider. We're currently operating in Las Vegas and San Francisco, with Austin and Miami on the horizon, and testing underway across seven U.S. markets. About Our Contract Student Worker Program Zoox's contract student worker program puts you at the center of one of the most ambitious challenges in transportation. You'll contribute to real projects, work alongside engineers and researchers pushing the boundaries of autonomous technology, and gain experience that goes well beyond the classroom. We're looking for students who bring strong academic foundations, curiosity that doesn't stop at coursework, and a drive to be part of something that matters. Role Overview As a Data Scientist focused on forecasting, you will help Fleet Operations anticipate the resources required to scale an autonomous vehicle service across markets. You will develop forecasting and scenario-planning capabilities across fleet availability, supply, staffing, operational demand, charging, and infrastructure. Your work will inform high-impact planning decisions and create a shared, data-driven view of future operational needs. Responsibilities Develop forecasting models for fleet availability, supply hours, staffing, operational workload, charging demand, and infrastructure needs Convert spreadsheet-based planning processes into reproducible, scalable, and well-documented analytical workflows Evaluate model performance through backtesting, forecast-versus-actual reporting, and clearly defined accuracy measures Required Qualifications <li