
Stripe · Toronto
WHO WE ARE ABOUT STRIPE Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ...
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the
most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission
is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented
opportunity to put the global economy within everyone's reach while doing the most important work of your career.
Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the
models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a
passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is
broad and varied, influencing how our products work (e.g., understanding user needs, preventing fraud, or optimizing charge
flows), how our business works (forecasting key outcomes, managing liquidity, and quantifying risk exposure), how our go-to-market
motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal
effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to
the most relevant team based on your background.
We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and
Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and
leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company
strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical
modeling, causal inference, optimization, experimentation, and all forms of analytics.
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you
are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
analytics, causal inference, and experimentation
Operations Research)
About the Company At Avaron, you get the security of permanent employment combined with the variety of working at different customers. We place specialists across everything from tech, IT and industry to project management and business support – and whatever the assignment, you have a consultant manager who is there for you and your development. About the Role You will take a key role in strengthening and scaling a production-grade optimization solution in a data-intensive environment. The work combines advanced analytics, Linear Integer Programming, and MLOps, with a strong focus on making models reliable in production rather than only building prototypes. You will work across the full flow in a sophisticated Python codebase, from data wrangling and model improvement to deployment, monitoring, and stakeholder dialogue. This role is a strong fit if you enjoy turning complex business needs into robust technical solutions and want to influence how optimization models evolve in production. Job DescriptionYou will maintain and improve the existing optimization model by identifying limitations and implementing enhancements. You will present model outputs and analytical insights to stakeholders, turn business needs into technical solutions, and continuously incorporate feedback into the product. You will help ensure that the deployed AI product on GCP remains robust, efficient, and reliable through monitoring and ongoing maintenance. You will improve data preparation and wrangling pipelines and integrate additional data sources to strengthen model inputs. You will collaborate with Data Scientists, ML Engineers, and Product Managers to improve the performance, scalability, and reliability of the optimization solution. You will implement MLOps practices for deployment, monitoring, and lifecycle management of machine learning models. You will perform ad hoc analyses and create visualizations that support data-driven decisions across teams. RequirementsSolid knowledge of discrete optimization models, including Integer Programming and Mixed Integer Programming Strong Python skills and the ability to write clean, efficient, modular, and production-ready code Experience developing and deploying machine learning models in the cloud, with strong knowledge of GCP Hands-on experience with MLOps and CI/CD pipelines in a production environment Strong SQL skills for data manipulation and analysis Ability to understand diverse data sources and build robust data wrangling and aggregation pipelines Familiarity with DBT for data transformation Good understanding of software architecture and experience maintaining AI models in production Ability to communicate results clearly, translate stakeholder needs into technical solutions, and work effectively in Agile cross-functional teams What We OfferPermanent employment at Avaron AB Occupational pension Wellness allowance of SEK 5,000 per year Application Selections are made on an ongoing basis – apply as soon as you can.
At Toyota Material Handling Europe, we create the technology that keeps the world moving. We are over 13,500 colleagues passionate about supporting companies of all sizes with todays and tomorrow's material handling challenges. Because we know that our business and our industry are essential and sometimes even critical for them, for daily life and society at large. In our respective headquarters in Mjölby, Sweden, Willebroek, Belgium, in our Sales companies across Europe or in our factories in France, Italy and Sweden, you can be part of an extraordinary journey. And together, we will Move the world towards easy and sustainable. The Position At Toyota Material Handling Europe, we are accelerating our journey towards becoming a data-driven and AI-enabled enterprise. As part of this transformation, we are looking for a Data Scientist with strong engineering capabilities to join our Data & Advanced Analytics organization. In this role, you will focus on designing, developing, deploying, and operating AI/ML solutions at enterprise scale, leveraging Snowflake and Snowpark as the core platform. You will play a key role in moving from analytics-driven insights to production-grade, AI-powered solutions embedded in business processes. You will work in a product-oriented setup, collaborating with cross-functional teams to deliver AI-enabled data products that create measurable business value across the organization. You will report to Head of Data and Advanced Analytics. Your Responsibility As a Data Scientist in our team, you will work across the full AI/ML lifecycle: Data Science & AI Solution Development Design, develop, and deploy machine learning models and advanced analytics solutions, owning the full lifecycle from exploration to production Apply statistical and AI/ML techniques to solve business problems, continuously improving models to maximize impact MLOps & Engineering Practices Operationalize models into scalable, production-grade solutions using MLOps best practices (CI/CD, automation, monitoring, and retraining) Ensure reliability, scalability, and performance of ML solutions in collaboration with Data Engineering teams Data Platform & Collaboration Work with modern data platforms (e.g., Snowflake) to build scalable data and AI solutions in close collaboration with cross-functional teams Translate business needs into technical solutions and contribute to shared frameworks, standards, and best practices Business Impact & Stakeholder Engagement Partner with stakeholders and product teams to identify use cases, deliver insights, and drive data-informed decisions Communicate findings and recommendations clearly to both technical and non-technical audiences Governance & Continuous Improvement Contribute to responsible AI, data quality, and governance practices across the ML lifecycle Stay up to date with industry trends and support the growth of a strong, data-driven culture Your Profile Proven experience as a Data Scientist (or similar role), with hands-on expertise in developing and deploying machine learning models in production environments Strong programming skills in Python and SQL, with experience in data manipulation, statistical analysis, and ML frameworks Solid understanding of the full ML lifecycle, including model development, deployment, and monitoring Experience working with modern data platforms and cloud environments, preferably Snowflake Knowledge of MLOps practices, including versioning, CI/CD pipelines, and model performance monitoring Ability to translate complex business problems into data-driven solutions and communicate insights clearly to stakeholders Strong collaborative mindset, with experience working in cross-functional teams alongside Data Engineers, Analysts, and business stakeholders Curious and proactive approach, staying up to date with the latest developments in AI/ML and contributing to a data-driven culture Degree in Data Science, Computer Science, Statistics, Mathematics, or a related field Fluent in English (Swedish is a plus) Our Offer At Toyota Material Handling Europe, we're not just a global leader in a fast-paced industry - we are a team that values collaboration, growth and making a real impact for our customers. In our dynamic, diverse and international environment, we offer a workplace where you can truly thrive and bring your ideas to life. This position is based at our European Headquarters in Mjölby, Sweden with remote work options available up to two days a week. We're committed to supporting you with an attractive benefits package, including a yearly bonus and flexible work arrangements that allow you to balance your personal and professional life. With clear goals and direction from senior leadership, you'll also find abundant opportunities for career growth and development within the company. Our organisational support ensures that you can maintain a healthy work-life balance while pursuing meaningful work that shapes the future of our industry. At Toyota Material Handling Europe, we believe in continuous learning and provide plenty of opportunities to develop new skills and take on exciting projects. Collaboration is at the heart of everything we do, and we take pride in fostering a supportive, open environment where every voice is heard. Your Application Submit your application in English no later than August 9th, 2026. Applications only accepted through our recruitment system. We screen continuously, so do not miss out and send in your application today! Interviews will start in August/September 2026. If you need support with your application or have questions about the recruitment process, please contact Victoria Östryd Söderlind Recruitment Specialist; Victoria.OstrydSoderlind@toyota-industries.eu
Company description: Who are we?Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent. We are constantly pushing our own skills and abilities to drive change in the automobile industry like never before. We are looking for innovative, committed people to join us in this endeavour and create safe, sustainable and connected cars. We believe in the power of people and will challenge and support you to reach your full potential. Join us and be part of Volvo Cars’ journey into the future. Job description: Let's introduce ourselves The Engineering Data Hub at Volvo Cars accelerates the use of data, analytics, and AI. Our cross‑functional team of data, software, and machine learning engineers combines technical expertise with a collaborative mindset to transform large‑scale vehicle data into actionable insights. We support the development of new products, functions, and services by analyzing complex data sources, building machine‑learning models, developing scalable cloud pipelines, creating intuitive visualizations, and create Generative AI products. Our culture focuses on learning, inclusion, and achieving success together! What you'll do As a data scientist, you will turn data into meaningful insights using analytics and machine learning techniques. You are comfortable working independently on innovative projects to require, amongst others, to design, train and evaluate models to analyze sensor signals and other engineering data. You will collaborate closely with other data scientists and data engineers across different disciplines. You’ll contribute by sharing your knowledge and learning from others as you help evolve our methods, tools, and best practices. This role suits someone who enjoys building, exploring, and delivering high‑quality analysis that drives real impact. What you'll bring You have a strong quantitative background, with a Master’s in Statistics, Mathematics, Data Science, Computer Science, or a related field, along with 3+ years of experience in a data science or similar role. You have experience in all stages of data science projects: framing questions, analyzing data, modeling, interpreting results, and communicating insights. You may have experience in several of the following areas (you do not need to meet all of them): Experience with Python and aware of software and data engineering practices for production systems Familiar with the standard data science toolkit (e.g., pyspark, Pandas, Scipy, Numpy etc.) Experience building data pipelines on platforms such as Databricks or Snowflake Understanding and experience applying in statistical modeling, inference, time-series analysis, and machine learning algorithms Understanding of CI/CD principles, particularly for data or ML pipelines Experience with developing generative AI or LLM-based applications Beneficial to have: Familiar with front-end development (e.g., Streamlit or React) Experience with cloud-environments ‑ (preferably Azure) Automotive or mechatronic domain knowledge We value how you collaborate as much as your technical skills. You should approach problems with curiosity and creativity as well as communicate clearly with both technical and non‑technical colleagues. You would take ownership and follow through as well as open discussions and multidisciplinary teamwork.