Casual Sales Assistant Jobs

​ Reformation is expanding, and we're on the lookout for passionate individuals to join our retail management team! If you're a dynamic leader with a commitment to sustainability and exceptional customer experiences, we want to hear from you. Even if there isn't a current opening in your area, submit your application to be considered for future Store Manager roles as we grow. Who We Are: Founded in 2009, Reformation is a revolutionary lifestyle brand that proves fashion and sustainability can coexist. We combine stylish, vintage-inspired designs with sustainable practices, releasing limited-edition collections for individuals who want to look beautiful and live sustainably. Setting an example for the industry, Reformation remains at the forefront of innovation in sustainable fashion—running the first sustainable factory in Los Angeles, using deadstock and eco fabrics, tracking and sharing the environmental impact of every product, and investing in the people who make this revolution possible. The brand has also established itself as a pioneer in retail innovation, developing an in-store tech concept that brings the best of its online experience to its physical doors. We are a future focused organization committed to the belief that the problems facing our planet and society can be solved through innovation, common sense and education. Being naked is the #1 most sustainable option. We're #2. Here at Ref, we put people first. We know that you can't innovate and do cool stuff without having everyone on board. So we work to create a culture where everyone feels like they belong and where their voices are truly valued. We build an inclusive culture together and make a real impact along the way. Benefits & Perks: Health, vision, and dental insurance for eligible employees Paid vacation, sick, holidays & volunteer time-off for eligible employees Mission based company + casual and entrepreneurial work environment Clothing discount, dog-friendly office,

​ Reformation is expanding, and we're on the lookout for passionate individuals to join our retail management team! If you're a dynamic leader with a commitment to sustainability and exceptional customer experiences, we want to hear from you. Even if there isn't a current opening in your area, submit your application to be considered for future Store Manager roles as we grow. Who We Are: Founded in 2009, Reformation is a revolutionary lifestyle brand that proves fashion and sustainability can coexist. We combine stylish, vintage-inspired designs with sustainable practices, releasing limited-edition collections for individuals who want to look beautiful and live sustainably. Setting an example for the industry, Reformation remains at the forefront of innovation in sustainable fashion—running the first sustainable factory in Los Angeles, using deadstock and eco fabrics, tracking and sharing the environmental impact of every product, and investing in the people who make this revolution possible. The brand has also established itself as a pioneer in retail innovation, developing an in-store tech concept that brings the best of its online experience to its physical doors. We are a future focused organization committed to the belief that the problems facing our planet and society can be solved through innovation, common sense and education. Being naked is the #1 most sustainable option. We're #2. Here at Ref, we put people first. We know that you can't innovate and do cool stuff without having everyone on board. So we work to create a culture where everyone feels like they belong and where their voices are truly valued. We build an inclusive culture together and make a real impact along the way. Benefits & Perks: Health, vision, and dental insurance for eligible employees Paid vacation, sick, holidays & volunteer time-off for eligible employees Mission based company + casual and entrepreneurial work environment Clothing discount, dog-friendly office,

​ Reformation is expanding, and we're on the lookout for passionate individuals to join our retail management team! If you're a dynamic leader with a commitment to sustainability and exceptional customer experiences, we want to hear from you. Even if there isn't a current opening in your area, submit your application to be considered for future Store Manager roles as we grow. Who We Are: Founded in 2009, Reformation is a revolutionary lifestyle brand that proves fashion and sustainability can coexist. We combine stylish, vintage-inspired designs with sustainable practices, releasing limited-edition collections for individuals who want to look beautiful and live sustainably. Setting an example for the industry, Reformation remains at the forefront of innovation in sustainable fashion—running the first sustainable factory in Los Angeles, using deadstock and eco fabrics, tracking and sharing the environmental impact of every product, and investing in the people who make this revolution possible. The brand has also established itself as a pioneer in retail innovation, developing an in-store tech concept that brings the best of its online experience to its physical doors. We are a future focused organization committed to the belief that the problems facing our planet and society can be solved through innovation, common sense and education. Being naked is the #1 most sustainable option. We're #2. Here at Ref, we put people first. We know that you can't innovate and do cool stuff without having everyone on board. So we work to create a culture where everyone feels like they belong and where their voices are truly valued. We build an inclusive culture together and make a real impact along the way. Benefits & Perks: Health, vision, and dental insurance for eligible employees Paid vacation, sick, holidays & volunteer time-off for eligible employees Mission based company + casual and entrepreneurial work environment Clothing discount, dog-friendly office,

About the Team The DoorDash Kitchens team is a part of DoorDash's New Delivery Models and launches and operates shared 'dark kitchens' for restaurateurs looking to grow their business. This is a small but mighty team helping scale DoorDash Kitchens. About the Role You’ll work in our development kitchen testing recipes for new concepts, while maintaining a clean kitchen area, and organization in our DoorDash operated kitchen. You will collect, clean, and distribute cookware throughout your shift, and set the example for keeping the kitchen spotless. You will receive and organize inventory, and support the development team with daily food prep and projects. You will help maintain general kitchen pars, report shortages and inform the manager when items need to be reordered. You will maintain kitchen cleanliness, comply with food sanitation requirements by properly handling food and ensuring correct storage, and clean and sanitize cooking surfaces at the end of the shift. You will report to the Executive Development Chef. You’re excited about this opportunity because you... Love to work on a team and contribute to team culture Believe no project is too big or small Are cuisine-curious and love to cook across multiple culinary concepts Want to work in new restaurant models including delivery-only environments. We’re excited about you because… You have 1 year or more experience as a dishwasher, prep cook or line cook in a high volume kitchen environment including fast-casual, QSR, and from-scratch restaurants You have experience receiving and organizing restaurant inventory using the FIFO method You have experience preparing food from scratch, making hot and cold sauces, and have basic knife skills You are ServeSafe certified (or are willing to become certified) and you take initiative to keep the whole kitchen clean, if you see something that requires attention you take action, you don’t leave it for the next person You are highly organized,

Description: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Quantitative Researcher for our team in Singapore. This team trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. As a Quantitative researcher your responsibilities will include Develop new or improve existing trading models using in-house platforms Use advanced mathematical techniques to model and predict market movements Analyse large financial datasets to identify trading opportunities Provide real time analytical support to experienced traders Requirements : Possess a degree in a highly analytical field, such as Engineering, Mathematics, Computer Science from top ranked universities Quantitative bent of mind A working knowledge of Linux/Unix Programming experience, preferably in C++ or C No prior knowledge of financial markets is needed but must have a strong interest in learning about financial markets. Have a strong work ethics Benefits: Our open and casual work culture gives you the space to innovate and deliver. Our cubicle free offices , disdain for bureaucracy and insistence to hire the very best creates a melting pot for great ideas and technology innovations. Everyone on the team is approachable, there is nothing better than working with friends! Our perks have you covered. Competitive compensation 4 Weeks of paid vacation Regular after work parties Top of the line health insurance for family International team outing

About the Team The DoorDash Kitchens team is a part of DoorDash's New Delivery Models and launches and operates shared 'dark kitchens' for restaurateurs looking to grow their business. This is a small but mighty team helping scale DoorDash Kitchens. About the Role You’ll prepare the meal and upkeep the high standard of our merchant partners/brands, while maintaining a clean kitchen area, and organization and storage for multiple culinary concepts in our DoorDash operated kitchen. You will collect, clean, and distribute cookware throughout your shift, and set the example for keeping the kitchen spotless. You will receive and organize inventory, and support other cooks and kitchen managers with daily food prep and projects. You will help maintain general kitchen pars, report shortages and inform the manager when items need to be reordered. You will maintain kitchen cleanliness, comply with food sanitation requirements by properly handling food and ensuring correct storage, and clean and sanitize cooking surfaces at the end of the shift. You will report to the Kitchen Manager. You’re excited about this opportunity because you... Love to work on a team and contribute to team culture Believe no project is too big or small Are cuisine-curious and love to cook across multiple culinary concepts Want to work in new restaurant models including delivery-only environments. We’re excited about you because… You have 1 year or more experience as a dishwasher, prep cook or line cook in a high volume kitchen environment including fast-casual, QSR, and from-scratch restaurants You have experience receiving and organizing restaurant inventory using the FIFO method You have experience preparing food from scratch, making hot and cold sauces, and have basic knife skills You are ServeSafe certified (or are willing to become certified) and you take initiative to keep the whole kitchen clean, if you see something that requires attention you take action, you don’t lea

About the Team DoorDash is building the next generation of causal decisioning systems for New Verticals: grocery, convenience, retail, alcohol, pets, flowers, and other emerging categories. These businesses operate in high-dimensional, dynamic marketplaces where every consumer, merchant, item, promotion, substitution, search result, and delivery promise creates a causal question. We are hiring a Principal Machine Learning Engineer to lead the Causal ML pod and establish the technical foundation for company-level causal decisioning. This is a senior technical leadership role for a practitioner who has built consequential causal systems in production and can turn ambiguous business questions into a coherent measurement and decision platform. A central mandate is to define and build a durable company-level causal value metric: a trusted, long-term signal that estimates the incremental value created by product, growth, and marketplace actions. The metric will connect experiments, observational evidence, and production ML so leaders and product teams can compare investments on a common basis while protecting customer experience and marketplace health. About the Role You will set the multi-year technical direction for causal ML, lead the pod’s portfolio and operating model, and remain close to the hardest modeling and systems work. You will be accountable for both scientific credibility and production impact. You’re excited about this opportunity because you will… Lead the Causal ML pod across technical strategy, architecture, execution, and quality. Create a roadmap that joins foundational platform work with high-value product applications. Define the company-level causal value metric and its measurement framework, including the target construct, time horizon, component outcomes, identification strategy, calibration, uncertainty, and guardrails. Build the metric into a decision system that teams can use for product prioritization, experiment readouts, intervention select

About the Team DoorDash is building the next generation of causal decisioning systems for New Verticals: grocery, convenience, retail, alcohol, pets, flowers, and other emerging categories. These businesses operate in high-dimensional, messy marketplaces where every consumer, merchant, item, promotion, substitution, search result, and delivery promise creates a causal question. About the Role We are hiring a Causal Machine Learning Engineer to help build the causal ML foundation behind how DoorDash grows New Verticals. This is not a generic ML role with some experimentation work on the side. We are looking for someone who has built or deeply worked on production causal systems: uplift models, heterogeneous treatment effect models, surrogate metrics, experimentation platforms, counterfactual policy evaluation, promotion optimization, or marketplace decisioning systems. You will join a small, senior pod of causal ML and econometrics experts working across ML, Analytics, Product, and Engineering. The mandate is to build the causal spine for a large-scale consumer marketplace. You're excited about this opportunity because you will… Design, build, and productionize causal ML systems that influence real marketplace decisions across New Verticals. Build uplift / heterogeneous treatment effect models for consumer lifecycle value, promotions, retention, and reactivation. Develop counterfactual evaluation frameworks for ranking, recommendations, search, promotions, substitutions, and marketplace interventions. Build systems that connect experimentation, observational data, and ML decisioning so teams can make better tradeoffs when randomized experiments are slow, noisy, or incomplete. Design surrogate metrics and early indicators that help teams move faster while preserving long-term marketplace health. Partner with econometrics and analytics leaders to choose the right methods: doubly robust estimation, IV, diff-in-diff, synthetic controls, double ML, CUPED-style variance re

About the Team DoorDash is building the next generation of causal decisioning systems for New Verticals: grocery, convenience, retail, alcohol, pets, flowers, and other emerging categories. These businesses operate in high-dimensional, messy marketplaces where every consumer, merchant, item, promotion, substitution, search result, and delivery promise creates a causal question. About the Role We are hiring a Causal Machine Learning Engineer to help build the causal ML foundation behind how DoorDash grows New Verticals. We are looking for someone who has built or deeply worked on production causal systems: uplift models, heterogeneous treatment effect models, surrogate metrics, experimentation platforms, counterfactual policy evaluation, promotion optimization, or marketplace decisioning systems. You will join a small, senior pod of causal ML and econometrics experts working across ML, Analytics, Product, and Engineering. The mandate is to build the causal spine for a large-scale consumer marketplace. You're excited about this opportunity because you will… Design, build, and productionize causal ML systems that influence real marketplace decisions across New Verticals. Build uplift / heterogeneous treatment effect models for consumer lifecycle value, promotions, retention, and reactivation. Develop counterfactual evaluation frameworks for ranking, recommendations, search, promotions, substitutions, and marketplace interventions. Build systems that connect experimentation, observational data, and ML decisioning so teams can make better tradeoffs when randomized experiments are slow, noisy, or incomplete. Design surrogate metrics and early indicators that help teams move faster while preserving long-term marketplace health. Partner with econometrics and analytics leaders to choose the right methods: doubly robust estimation, IV, diff-in-diff, synthetic controls, double ML, CUPED-style variance reduction, contextual bandits, off-policy evaluation, and related approaches

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. Role Overview: As a Data Scientist, you will help measure the impact of PlayStation's products, features and commercial initiatives through experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will apply robust analytical techniques to solve complex business problems, generate actionable insights and support evidence-based decision-making across PlayStation. This role goes beyond traditional A/B testing. You will apply modern causal inference, statistical modelling and machine learning techniques to evaluate initiatives where controlled experiments are difficult or impossible, collaborating closely with product, engineering, analytics and business teams to deliver high-quality measurement and insights. This is an opportunity to work on high-impact initiatives affecting millions of PlayStation players while developing your expertise in experimentation, causal inference and applied data science. What You'll Be Doing: Apply measurement methodologies across experimentation, causal inference and advanced analytics to evaluate product and commercial initiatives. Design and execute robust measurement approaches across randomised experiments, quasi-experimental metho

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

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. Role Overview: As a Senior / Staff Data Scientist, you will help shape how PlayStation measures the impact of products, features and commercial initiatives through world-class experimentation, causal inference and applied data science. Working at the intersection of data science, machine learning, product and commercial strategy, you will develop innovative measurement methodologies, define best practices, and provide technical leadership that enables teams across PlayStation to make faster, more confident business decisions. This role goes beyond traditional A/B testing. You will solve complex measurement problems where controlled experiments are difficult or impossible, applying modern causal inference, statistical modelling and machine learning techniques to generate robust business insights. You will collaborate closely with product, engineering, analytics and business teams to raise the standard of experimentation and evidence-based decision-making across the organisation. This is an opportunity to influence strategic decisions impacting millions of PlayStation players while helping establish best-in-class measurement practices across one of the world's leading entertainment companies. What You'll Be Doing: Develop innovative measurement methodologies across

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 Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make. We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization. The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,