Data Instructor Jobs

The Music Mission enables Music creators to grow, engage & monetize their fan bases on Spotify. Central to the Music Mission's vision is the development of promotional tools for artist and label teams, powered by Spotify's deep knowledge of listener behavior. Products like Discovery Mode, Marquee, Showcase, Music Videos and Clips enable artists and their teams to grow, monetize and connect with their audience. We're looking for a Data Scientist to join Discovery Mode, part of the Music Mission. Discovery Mode helps artists and music marketers reach new listeners when it matters most. Artists and labels flag priority songs, and our system feeds that signal into the algorithms behind personalized playlists. In this role, you'll partner with product, engineering, and user research to build the technology that powers Discovery Mode. Your focus will be customer engagement and reporting — understanding what customers need, building instrumentation and dashboards for our self-serve product, and running experiments that improve the experience and drive business impact. As part of the Product Insights team, you'll help define the next generation of promotion products for the music industry. What You’ll Do Work closely with cross-functional teams of data scientists, researchers, product owners, engineers, designers, marketers, and others across the company to develop the next generation of promotion tools for artists. Identify the most impactful opportunities for product development based on user needs, and execute on them diligently and resourcefully. Define metrics and build the dashboards we use to measure the health and success of our products. Partner closely with other data scientists to inform, build and test hypotheses that deliver actionable insights to improve and expand our products. Contribute to a community of data scientists by evolving best practices and learning new skills. Maintain a culture of rigor an

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes. Agentic AI and LLM Development: Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization. Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications. Assist in implementing tool-using capabilities, function calling, and agent memory systems. Software Engineering and Productionalization: Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments. Optimize for performance, latency, and token efficiency. Collaborate with senior team members on testing, deployment, and monitoring. Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders Integ

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Key Responsibilities Yield & Process Optimization: Collaborate with semiconductor manufacturing engineering teams to analyze inline/param/probe data to identify top yield detractors and drive continuous improvement. Data Pipeline & Automation: Extract, cleanse, and analyze datasets from SQL databases, sensor networks, and fabrication tool logs to support semiconductor manufacturing operations. Advanced Analytics & Modeling: Apply data science techniques, statistical modeling, and machine learning to solve yield issues and support defect reduction strategies. Experimentation Support: Assist process and integration engineers in running and analyzing Design of Experiments (DOE) to enhance process capabilities and margins. Visualization & Communication: Develop automated reports and dashboards using visualization tools (e.g., Dash, Plotly, Angular) to communicate technical concepts and project outcomes effectively to engineering stakeholders. Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. Contributes to a culture of continuous improvement by identifying, testing, and

We are seeking a highly skilled and experienced Data Scientist to join our Perception Verification and Validation team. The team is responsible for verifying and validating the perception stack of our autonomous driving system. The candidate will work closely with other data scientists, perception engineers, and systems engineers to develop datasets and metrics to quantify the performance of our perception system. The candidate will also help define key performance metrics that will enable perception engineers to directly measure the impact of new features on both the overall Perception stack as well as end-to-end system behavior. In this role, You will... Define key performance metrics that will help perception engineers to measure the impact of new features on the perception stack and the end-to-end system behavior Create and maintain datasets used to evaluate the perception stack and end-to-end driving performance. Analyze large scale metric results to identify patterns and insights about perception failure modes. Present results and insights to leadership. Design and implement statistical methods to quantify uncertainty in our performance and validation metrics. Qualifications Master's or PhD degree in Statistics, Mathematics, Computer Science, or a related field Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code Basic experience with autonomous driving, safety-critical systems, or computer vision systems. Proficient in exploratory data analysis (EDA) and data visualization to understand and present trends and their implications for the business. Background in statistical modeling and analysis; including experience making data-driven decisions that connect point and uncertainty estimates to business impact. Bonus Qualificati

We’re looking for a hands-on Data Center Engineer to help us test, standardize, maintain, and improve server and network hardware for our globally distributed trading infrastructure. The role combines lab validation with hardware lifecycle operations: maintenance planning, coordinating onsite work with providers/contractors, ensuring quality execution and maintaining inventory. Travel will be required for deployments or complex troubleshooting. What You’ll be doing Test and compare server and networking hardware configurations (performance, stability, compatibility) Own hardware acceptance: burn-in checks, firmware/BIOS baselines, and “known-good” configs Plan and coordinate hardware maintenance and upgrades across sites (schedules, checklists, validation steps) Work together with onsite providers/contractors to execute installations and maintenance; review evidence and ensure quality Produce clear documentation: test results, approved SKUs, configuration standards, and maintenance runbooks Help troubleshoot hardware issues and support spares/RMA decisions Maintain inventory documentation What we look for in you: Solid understanding of server hardware basics (CPU/RAM/storage, NICs, firmware/BIOS, FPGA) and networking fundamentals Basic Linux skills for testing/benchmarking Accuracy and high level of attention to details Ability and willingness to solve problems in non standard way Structured troubleshooting mindset Comfortable coordinating work with external parties and driving tasks to completion. Able to document results and make recommendations based on data Willingness to travel internationally from time to time Nice-to-Have: Bare-metal fleet experience or lab/burn-in testing background Optics/cabling validation knowledge Experience with vendor/procurement coordination (RMAs, substitutions, lead times) Why should you join our team? Exciting challenges with ample opportunities for personal and professional growth A welcoming international team of highly qualified

About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform is comprised of three products: THG Commerce, THG Studios, THG Fulfilment. Each represents a single, unified solution, overcoming challenges and taking brands direct-to-consumer. Our client portfolio includes globally recognised brands such as Coca-Cola, Nestle, Elemis, Homebase, and Proctor & Gamble. The Role We are seeking a talented and commercially astute Data Scientist to join our dynamic team tackling Fraud, Payments and Finance. In this multi-focus role, you will be responsible for protecting our global e-commerce operations from fraud, optimising our payments performance and driving profitability and automation initiatives within Finance. Working with vast, complex datasets, the work will involve combatting online fraud using our award-winning THG Detect platform and driving payments optimisation by increasing authorisation rates, while also using the latest AI software and Google Cloud Platform (GCP) infrastructure to build complex data solutions and applications. This role requires a blend of strong technical skills, commercial acumen, and effective communication to translate complex data insights into tangible business value. Responsibilities: Optimise Fraud Detection: Continuously improve automated decision-making in our in-house THG Detect platform using machine learning and decision rules. Enhance Payment Performance: Lead data-driven initiatives to boost payment authorisation rates, optimise transaction routing, and reduce costs. Drive Profitability within Finance: Lead automation and profitability initiatives across different areas of Finance. Communicate Performance: Report on all aspects of fraud, payments and finance performance to stakeholders at all levels, including C-level management. Drive System Improvements: Collaborate with Fraud, Payments, F

Please note we are looking to speak to individuals already based in the Doha as a first priority. Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising of over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with unrivalled industry knowledge to deliver end-to-end data-driven solutions and fast-track digital initiatives for banking and payments, capital markets, wealth and asset management, insurance, and the energy sector. Capco’s cutting-edge ingenuity is brought to life through its Innovation Labs and award-winning Be Yourself At Work culture and diverse talent. Data Engineer (Snowflake) Location: Doha | Practice Area: Data & Analytics | Type: Permanent Shape the future of data platforms by delivering modern, cloud-native engineering solutions that enable leading financial institutions to unlock the full value of their data. The Role Capco is a global technology and business consultancy, focused on the financial services and energy sectors. We combine innovative thinking with deep industry expertise to help our clients solve complex business and technology challenges. We are looking for a Senior Consultant Data Engineer with strong Snowflake expertise to join our growing Data & Analytics practice in Doha. You will work closely with clients to design, build and optimise modern cloud-based data platforms, enabling advanced analytics, regulatory reporting and data-driven decision-making. As a Senior Consultant, you will combine technical delivery with client engagement, helping organisations modernise their data landscape while mentoring junior colleagues and contributing to Capco's collaborative consulting culture. What You'll Do Design, develop and optimise scalable data pipelines and cloud-native data platforms using Snowflake and mod

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Data Engineer on the Data Science & Analytics team, you will build the data foundation for Anthropic’s quote-to-cash lifecycle: the path a deal takes from opportunity through revenue. You will design the canonical data models so that Sales, Deal Desk, Order Management, Revenue Operations and Finance work from one governed, auditable definition of what was sold, on what terms, and where each deal stands. You will partner closely with DS&A and with GTM and Finance systems teams who own Salesforce, CPQ and billing to make quote-to-cash data reliable, well-modeled and self-serve as our business scales. Responsibilities Understand the data needs of Deal Desk, Order Management, Revenue Operations, Finance and Sales systems teams, and translate them into technical requirements Design, build and own data models that transform raw Salesforce, CPQ, and billing data into canonical datasets Establish high data integrity standards and SLAs to ensure timely, accurate delivery of data Partner with Salesforce, CPQ and billing engineers on upstream schema changes, new fields and ingestion so the warehouse faithfully mirrors the systems of record Build foundational data products, dashboards and tools to enable self-serve analytics to scale across GTM teams Influence stakeholder roadmaps from a data perspective, and become the expert on Anthropic’s GTM data models and architecture You might be a good fit if you have 5+ years of experience as a Data Engineer, Analytics Engineer or in a similar Data Science & Analytics role, ideally partnering with GTM, Revenue Operations or Finance teams. A passion for the company's missio

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. As a Data Science Intern on the Strategy, Execution, & Analytics team within the Platform group, you'll partner with product and engineering teams to turn data into decisions that drive real business impact. This team builds analytics models and systems that scale insights across Coinbase and directly into the product. You'll collaborate with senior data scientists and business partners to design experiments, build models, and deliver data-driven recommendations that shape how millions of customers experience crypto. You will gain hands-on experience at a publicly traded crypto-native company, with mentorship from senior data scientists and direct exposure to how data shapes the company. What you'll do: Collaborate with product teams to create analyses and build models that drive measurable business outcomes. Support the design and execution of experiments, including A/B tests and causal inference methods. Build and maintain analytical datasets and pipelines that ensure data integrity and power your analyses and models. Distill complex analyses into clear, actionable insights through data-driven storytelling for technical and non-technical audiences. Partner with senior team members on analytical deep dives to diagnose and address complex business problems. Required Skills and Experience: Coursework or project expe

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. As a Data Engineer Intern within the Platform product group, you'll partner with analytics engineering to build and maintain the data pipelines and infrastructure that power insights across Coinbase. You'll work alongside senior engineers and cross-functional partners in product and engineering to ensure data accuracy, scalability, and accessibility for analytical and machine learning use cases. What you'll do: Build and maintain data pipelines that ensure data integrity and accessibility for analytics and machine learning workloads Support the development of scalable data infrastructure using Python and cloud-based technologies Integrate and manage data from multiple sources, including internal systems and external APIs Contribute to analytical deep dives with senior team members, translating findings into clear documentation and recommendations Learn and apply data engineering best practices including data governance, security, and performance optimization Required Skills and Experience: Completed or in-progress coursework in Computer Science, Data Engineering, or equivalent experience with demonstrated programming proficiency in Python, including data structures and algorithms Hands-on experience writing SQL for data analysis and working with relational database concepts Familiarity with cloud platforms (AWS, GCP, o

About Backblaze Backblaze is the object storage leader in the open cloud movement, fueling customer success with cloud storage built purposefully to unlock budgets, unburden administrators, and unleash innovators. Together with our partners, we’re helping customers break free from the restrictive, overpriced legacy solutions that hold them back, and blaze forward with the full power of the open cloud in their hands. Founded in 2007, we scaled the business with less than $3 million in outside funding until 2021, when we did a traditional IPO on the Nasdaq stock exchange. Today, Backblaze generates over $100m in revenue and is the leading specialized storage cloud - managing over three billion gigabytes of data storage for 500K+ customers in 175+ countries, including businesses, developers, IT professionals, and individuals. But while there is a lot to celebrate in our past, there is almost as much opportunity ahead of us. We’re seeking a Data Center Technician to join our team! About the Role: Individuals fulfilling this role will be responsible for managing, maintaining, and optimizing the physical infrastructure of our data center operations. The ideal candidate will have significant technical knowledge of server hardware, networking equipment, power and cooling systems, and structured cabling. This role requires a proactive problem-solver with strong leadership abilities, deductive reasoning, and a focus on operational excellence. What You'll Do: Hardware Deployment & Maintenance: Maintain organizational infrastructure including racking equipment, replacing hard drives and other system components Troubleshoot, repair, and replace defective equipment with minimal supervision Help manage onsite inventory of hard drives, cables, rails and other spare parts RMA defective components Setup, test and activate new equipment via the Linux command line Data Center Operations: Work as Backblaze’s physical presence in Data Center Operations On-call responsibilities requir

Apply early for priority consideration. Gallup has limited openings for this internship, and the position will be filled quickly. As a data engineering intern at Gallup, you’ll help build and modernize the data tools, infrastructure and pipelines that enable teams to work with data at scale. Alongside experienced technical leaders, you’ll put your Python and SQL skills to work on meaningful projects while learning best practices, experimenting with modern tools and seeing firsthand how strong data engineering supports better decisions. What You’ll Do During your internship, you will: Build foundational data tooling and infrastructure designed to scale as the volume and frequency of data grow Help modernize legacy data pipelines using Python, SQL and Gallup’s evolving data platform Troubleshoot data quality issues in large, imperfect datasets Apply data engineering practices to move, transform and validate data across systems Help build reliable, efficient data workflows Learn from senior technical leaders who will mentor you on engineering practices, tools and approaches Collaborate with engineers and interact directly with stakeholders to understand needs and deliver useful solutions Use AI-enabled development tools to improve the quality and efficiency of your work What You Need Enrollment in an associate, bachelor’s or graduate degree program in computer science, data engineering, information systems, statistics, math or a related field required Classroom or work experience writing SQL required, including joins, aggregations and troubleshooting query performance Classroom or work experience coding in Python for data processing, scripting or automation required Working knowledge of relational database and data modeling concepts, including schema design and dimensional or star-schema modeling, required Comfort using AI tools such as Claude, Claude Code or GitHub Copilot to support high-quality, efficient work required Understanding of ETL/ELT concepts and how data

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Data Engineer II to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Data Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: SQL / Python / Looker / Snowflake / dbt What you'll do: Build a scalable data system in which Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner Build processes supporting data transformation, data structures, metadata, dependency and workload management Develop and maintain data pipelines to collect, clean, and transform data (owning end to end data product from ingestion to visualization) Develop and implement data analytics models Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 4+ years of data engineering experience Working with cloud-based application development, and be fluent in at least a few of: Cloud services providers like AWS Data pipeline orchestration tools like Airflow, Dagster, Luigi, etc Big data tools like Spark, Ka

Qui sommes-nous ? Artefact est une société de conseil et d'ingénierie française spécialisée en data et IA, et leader en Europe, qui depuis plus de 10 ans est spécialisée dans la conception et le déploiement de technologies d’intelligence artificielle et de solutions data-driven. Basé à Paris, nous sommes aujourd’hui présents dans 27 pays sur tous les continents et comptons 2500 collaborateurs. Notre mission est d’aider les entreprises à exploiter tout le potentiel de l’IA et de la data en développant des solutions sur-mesure adaptées à leurs enjeux métiers. En tant que pionniers dans ce domaine, nous allions expertise technologique et excellence opérationnelle, en collaborant avec les plus grands acteurs du marché. Nos clients couvrent tous les secteurs clés de l’économie – industrie, retail, luxe, grande consommation, santé, finance – et incluent des grands groupes internationaux. En tant que Stagiaire Data Consultant , tu seras pleinement intégré(e) à une équipe de consultants. Ton rôle sera d'assister nos clients dans l'élaboration et la mise en œuvre de leur stratégie data, de la phase d'idéation jusqu'à l'implémentation. Tes missions pourront inclure : Cadrage / gestion des projets : interview clients et partenaires, mise en place de workshops, préparation des uses cases… Construction de roadmaps, d’analyses data-driven avec l’équipe projet et conception d'infrastructures en collaboration avec nos experts Orchestration du bon déroulement du projet, en appliquant le cas échéant les méthodes agiles (sprints planning et reviews, backlog refinement, démos…) Veille technologique et sectorielle : rester à l'affût des dernières tendances en matière de data et d'intelligence artificielle pour proposer des solutions innovantes. Communication : Préparer des présentations et des supports de communication pour les comités de direction et les équipes clientes. Processus de recrutement Étape 1 : Entretien RH avec notre chargée de recrutement, An

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. This is a full-time position offered exclusively on a Contract of Employment (Umowa o Pracę) . Please note that this is a hybrid role , requiring employees to work from our Warsaw office (Centrum Koneser) at least 3 days per week . We are not considering fully remote or B2B arrangements for this position. About Open Intelligence : We are the Activation arm of WPP Open Intelligence. Our team builds the foundational data infrastructure and high-performance edge services that power WPP’s position in the market. With approximately one-third of all global media spend flowing through WPP, our platform operates at the core of this massive network—deeply integrated and adopted by the largest supply-side partners in the AdTech industry.Operating at our scale presents unique engineering challenges. Our edge services currently handle over 60,000 classification requests per second, while our contextual classification pipelines process 10,000 requests per second. With operations spanning the US, UK, and ongoing expansion into EMEA and APAC, our infrastructure continuously interacts with up to 98% of the population