Casual Sales Assistant Jobs

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 Data Scientist - Experimentation & Measurement Overview: As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You’ll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products. What You’ll Be Doing: Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. Mentor and guide other Data Scientists, providing thought leadership and technical direction. Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication. Help define a

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 Data Scientist - Experimentation & Measurement San Mateo, CA (Hybrid) Overview: As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You’ll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products. What You’ll Be Doing: Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. Mentor and guide other Data Scientists, providing thought leadership and technical direction. Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results commu

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most comp

About the Team The Decision Systems team helps DoorDash teams make faster, more rigorous, and more trustworthy decisions. We build the analytical systems, statistical methods, and product experiences that power experimentation, causal inference, rollout analysis, metric interpretation, and business impact measurement across DoorDash’s three-sided marketplace. Curie is DoorDash’s experiment analysis product within Decision Systems. It sits at the center of how teams move from hypothesis to analysis to confident action, helping decision makers understand experiments, rollouts, metric movements, and marketplace impact while preserving scientific rigor, velocity, trust, and interpretability. Our work spans experimentation platforms, causal inference, variance reduction, switchback experimentation, metric systems, and AI-assisted analysis workflows. We partner closely with data scientists, engineers, product managers, and operators across DoorDash to translate advanced methods into reliable, scalable systems that improve decision quality and product velocity. Some of the work done in the team was published in articles such as: Design-Aware Variance Reduction for Switchback Experiments: A Comparative Study , Power-Optimal Covariate Adjustment for Switchback Experiments , CUPED on Steroids: Multivariate Covariate Adjustment for Switchback Experiments . About the Role We are looking for a Staff Applied Scientist to provide scientific leadership for DoorDash’s Experimentation Platform. In this role, you will define and advance the statistical, causal inference, machine learning, and AI capabilities that power high-quality decision-making across DoorDash. You will work on challenging problems at the intersection of experimentation, marketplace dynamics, machine learning, and product engineering. Your work will shape how DoorDash teams design experiments, analyze results, interpret noisy marketplace outcomes, and make faster, more trustworthy decisio

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in! At Duolingo, you’ll join a team that cares about educating our users, experimenting with big ideas, making fact-based decisions, and finding innovative solutions to complex problems. You’ll have limitless learning opportunities and daily collaborations with world-class minds — while doing work that’s both meaningful and fun. Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world. Read our blog to learn more. About the role You will... Derive insights from data to influence product roadmaps and drive business results Apply advanced analytical methods, structural approaches, causal inference, and/or machine learning and AI to model user behavior and estimate the impact of potential new feature implementations, and collaborate with product and engineering teams to develop solutions Evaluate product experiments to create and improve user experiences Communicate and present findings and recommendations to senior management Help preserve our culture of fact-based decision making as we scale You have... Pursuing a PhD degree (in at least the third year of PhD program) in a quantitative field (e.g. Economics, Finance, Statistics, Math, Linguistics, Computer Science, Computational Social Science, ML/AI), ideally planning to graduate in Fall 2027 or Spring/Summer 2028 Strong understanding of consumer digital products and an interest in applying advanced analytics and economics to business outcomes Previous experience analyzing large datasets, communicating results to technical and non-technical senior-level audiences, and making actionable recommendations that improve the product or business Skilled in SQL, R or Python, and/or statistical methods to analyze behavioral data Enthusiasm for learning and sharing analytical methods to h

Senior Data Scientist [Data] • [Vancouver, BC] We're looking for a Senior Data Scientist to help define Asana's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. As part of the AI organization within Asana you'll leverage data to influence how we should build our agentic work management products. Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling. 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 the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Work closely with Product Managers, User Researchers (UXR), and Engineers to understand the needs of our agentic work management customers, employing data frameworks and methodologies to understand our user segments and identify levers for driving user engagement Act as the data lead for specific AI features at Asana with product and engineering Use data analysis and data storytelling to identify key product opportunities for the roadmap Design experiments that measure product progress, and own key performance metrics. Collaborate with fellow Data Scientists in the team to research, identify and disseminate b

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE As a Data Scientist on the Digital Experience Insights team, you'll lead high-impact analytics initiatives, turning complex data, platform, and time-series data into rigorous predictive models, causal inferences, and strategic product metrics. You'll also apply advanced statistical and quantitative research methods to some of our most complex datasets, but the core of the role is turning that analysis into decisions leadership can act on. This role sits within a fast-moving analytics organization where the specific problems shift over time, so we're looking for someone with strong research rigor who can adapt it to whatever question is in front of them. WHAT YOU'LL DO Advanced Predictive & Statistical Modeling: Develop ML models spanning predictive modeling, time-series prediction, clustering, churn reduction, anomaly detection, and recommendation systems. Quantitative Research: Apply advanced computational methods and statistical techniques, including multilevel models and Statsmodels, to massive datasets. Executive Visualization: Create executive-level visual analytics that make complex findings accessible to senior stakeholders. Stakeholder Collaboration: Partner directly with Product, Engineering, and Business leaders to translate complex analytical findings into actionable strategy. We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in complia

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. 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, causal inference, economics, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive toolbelt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. Teams Hiring for this role: Foundation AI: Our AI evaluation team focuses on generating high-quality models and consistently improving our evaluation models. Safety: Managing account relationships and the real-time morphing of linguistic mapping. Economy: Drive creator success and growth by exploring marketplace structure and pricing. Engine: This team is dedicated to enhancing Roblox's overall stability and performance, enabling all its functionalities. Social: Analyze user engagement to identify areas for enhancing the user experience and delivering greate

Data Analyst - Investments Summary We are seeking an organised and self-motivated Data Analyst to work embedded in our Investments team, to help shape the development of one of the world's leading FinTech products. About the opportunity As a Data Analyst, you will enable our product and business segments in the Financial Empowerment domain, specifically Investments, to make data-driven decisions. You will monitor, measure and analyse the effectiveness of your product teams' initiatives, helping to drive the strategy of your business segment. You will apply robust analytical approaches, including experimentation and causal inference methods where appropriate, to understand the impact of product and business decisions on customer and business outcomes. You are here to establish a data mindset and thereby foster a culture of continuous learning and improvement. You will work in a cross-functional setup, collaborating closely with other analysts, engineers, designers, and product managers. In this role, you will: Help us set the right goals: Develop clear and measurable targets based on an initiatives’ scope. Improve our overall forecasting and goal setting capabilities. Handle stakeholders: Be an internal go-to-person for your teams when it comes to data related questions. Evaluate initiatives: Support product experimentation and impact measurement initiatives; design experiments and causal inference analyses, obtain cross-functional alignment, execute robust analyses, and deliver actionable insights. Share these learnings through clear documentation and concise, empathic communication. Contribute to self-serve data platform: Help building the right analytics foundations ,by pairing up with technical peers, so our product teams can interact with data and extract the right insights themselves. Provide monitoring tools: Build the dashboards your team looks at every week to make sure they are impacting our company OKRs. Improve data literacy

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Analytics organisation sits at the heart of Deliveroo powering decision-making across product, commercial and operations through experimentation and causal inference. We’re looking for a Senior Data Scientist to join our London team (working hybrid, 3 days in the office). In this role, you’ll enable high-quality human-led decision-making to maximise impact. We’re hiring multiple Senior Data Scientists across different areas of the business. Rather than hiring for one fixed team, we use the interview process to understand your strengths, interests and development areas, and then align you to the right scope, remit and team. About Our Analytics Organisation We have an outstanding analytics organisation, with a mission to enable the highest quality human and machine decision-making. Our community is highly active, with guest lectures, study groups, mentorship programmes and a robust technical review process. Data Scientists can progress equally as technical leads or people managers. Our data scientists come from all kinds of backgrounds but have excellence in common. Many are formally trained in data science, many are not. What You’ll Be Doing You will help answer questions like: Which markets/cities should we enter next? How can we incentivise good rider behaviour? What is the impact of exclusive deals we have with restaurants? How do we optimise our compensation policy to keep our customers happy and ordering with Deliveroo? What are the trade-offs we face when choosing between growth and profitability? How should we decide between them? How

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. The Data & Science Org At Deliveroo we have an outstanding data science organisation, with a mission to enable the highest quality human and machine decision-making. We work throughout the company - in product, business and platform teams - using analysis, experimentation, causal inference and machine learning techniques. We are uniquely placed to use data to help make better decisions and improve data literacy across Deliveroo. Data Scientists at Deliveroo report into our data science management team, and we have a highly active data science community, with guest lecturers, study groups, mentorship programmes, a robust technical review process, and plenty of opportunities to learn new things. Data Scientists can equally progress as technical leads (individual contributors) and as people managers. Our data scientists come from all kinds of backgrounds but have excellence in common. Many are formally trained in data science, many are not. We celebrate difference and have a dedicated data science diversity committee. As an Economist at Deliveroo you will help scale our business and improve the experience for restaurants, riders, and eaters. Using experimental or observational data, you will get to help answer questions like: Which markets/cities should we enter next? How can we incentivise good rider behaviour? What is the business impact of exclusive deals we have with restaurants? Can the Delivery food market sustain multiple players? What are the trade-offs we face when choosing between growth and profitability? How should we decide between them? What is the optimum selection and variety of restaurants? What impact do online reviews have? How will a change in the user i

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 Lyft Rider Science team is seeking an Applied Scientist intern to develop next-generation user simulation methods using state of the art AI methods. The goal of this project is to develop and validate LLM-based Rider Agents that can serve as behavioral proxies for real riders, and study when agent simulations can provide reliable signal about rider responses to product interventions before online experimentation. You will build agent-based simulation systems grounded in real rider context and behavioral data, evaluate their fidelity against observed rider behavior and historical experiments, and study where these simulations can accelerate product iteration and experimentation. This role combines LLM engineering, agent-based modeling, machine learning, and causal inference with direct applications to real-world rider products. The expected outcome is to build a working Rider Agent simulation prototype, establish an evaluation framework for measuring simulation fidelity and validate the framework using historical rider experiments. Responsibilities: Develop LLM-based Rider Agents that represent heterogeneous rider contexts, preferences, histories, and behaviors Build agent-based simulation environments for evaluating rider interactions with different product experiences and interventions Build evaluation pipelines to assess realism, robustness, and mechanism plausibility of simulated behavior against human data or established theory Analyze emergent behaviors and interaction dynamics in simulated populations under different user segment and marketplace conditions Conduct experiments and ablation studies on agent behavior, interaction dynamics, and simulation validity Apply the simulation framework to real Rider product problems and assess its usefulness for hypothesis generation, product iteration

About the Team The Experimentation Platform Team develops a state-of-the-art platform in industry that enables Product Engineers, Data Scientists, ML Engineers and non-technical audiences to come up with hypotheses; design, configure and analyze experiments; and conduct exploratory and causal analysis. At DoorDash, where we run thousands of experiments per year, our mission is to equip all decision makers with rigorous, data-driven insights by democratizing experimentation with quality and velocity. The team consists of a mix of experienced veterans of backend, web, statistical and data infra engineers and work closely with the data science community. Some of the interesting work done in the team was published in articles such as: Meet Dash-AB-The Statistics Engine of Experimentation at DoorDash Supporting Rapid Product Iteration with an Experimentation Analysis Platform The 4 Principles DoorDash Used to Increase Its Logistics Experiment Capacity by 1000% Improving Online Experiment Capacity by 4X with Parallelization and Increased Sensitivity About the Role If you want to solve the toughest engineering challenges, build cutting-edge experimentation products under rigorous operational constraints (high volume, correctness guarantees) and work with some of the smartest people in the industry, DoorDash’s Experimentation Platform is the right place for you. As a full stack engineer, you’ll build across our backend services, SDKs, and the Decision Portal UI used by thousands of internal users. Come join us and be part of the mission. You will report into the engineering manager on our Decision Experience team as part of the Decision Systems team. We expect this role to be hybrid (San Francisco, Sunnyvale, Seattle, New York) with some time in-office and some time remote. What You'll Do Work on dramatically enhancing and simplifying the Experimentation platform which is used by almost every engineer in the company. Have the opportunity to build a new Experimentation platf

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work