• Perform analyses, cross-checks and organize data to support decision-making. • Maintain and monitor existing dashboards, reports and automations. • Identify process improvement opportunities through data and technology. • Support the creation of analytical solutions and automations using various tools. • Participate in the structuring, validation and monitoring of KPIs. • Collect, clean and prepare datasets. • Collaborate with different teams to understand requests and translate needs into practical solutions. • Test new tools, artificial intelligence features and ways to increase efficiency in daily workflows. • Document processes, analyses and initiatives developed.

Role Description Support the execution of the Quality Lab Excellence and Quality Digital Transformation Roadmap. The role contributes to building a seamlessly connected digital quality ecosystem for Quality lab equipment. The role is remote and will be open with a fixed-term contract for 1 year. You will: - Operate within Global Quality Systems Management, including SAP QM, LIMS, and related platforms. - Support design, implementation, and continuous improvement of global Quality Systems to ensure data integrity, traceability, and performance tracking. - Act as a Quality Process Champion for SAP, ensuring alignment between Quality process requirements and corporate architecture. - Provide system user support, data analysis, and issue resolution contributing to continuous system enhancement. Digital Excellence and Data Governance: - Support the digitalization of global Quality lab processes and systems to enhance speed, transparency, and data quality. - Support the implementation of an end-to-end data management infrastructure, ensuring accuracy, consistency, and accessibility of quality data. - Support the development of data systems and dashboards for advanced analytics and decision making. - Drive continuous improvement initiatives across digital and system-related activities for scalability and sustained effectiveness. - Contribute to the creation of a fully integrated Digital Quality Ecosystem linking systems, laboratories, and global data sources. - Design, test, and deploy innovative digital tools and dashboards enabling real-time insights and predictive analytics. - Maintain structured repositories of knowledge and ensure consistent distribution and training across user communities. Laboratory Standards, Infrastructure, and Performance Excellence: - Support the implementation of efficiency and utilization measures in Quality Laboratory Equipment. - Participate in defining and validating Givaudan’s global laboratory meta-standards and best practices. - Facilitate knowledge and best practice sharing through the regional Quality Laboratory Coordinator Network. - Assist with training and knowledge transfer programs supporting Laboratory Excellence initiatives. - Collect and analyze key indicators to monitor laboratory performance, resource utilization, and process efficiency. Qualifications - Master’s or bachelor's degree in computer science, Data Science, Quality Management, Engineering, or related field. - Overall work experience minimum 1-3 years. - Solid project management skills and utilization of project management techniques. - Technical understanding of product life cycle management. - Good communication and stakeholder management skills. - Basic understanding of Flavours or Fragrance Quality Laboratory Processes and Principles. - Good understanding of SAP ECC. - Good understanding of Excel, Tableau, data analysis, and BI reporting. - Experience with database systems and ETL tools. Benefits - 37.5-hour week under the chemical industry collective agreement. - Flexible hours. - 30 days of vacation each year. - Parking facilities. - Modern canteen. - Leased bicycles. - Unlimited fresh fruit, water, coffee, and tea.

Role Description We’re looking for a Product Data Analyst to help our product teams make smarter, faster, and more data-driven decisions. In this role, you’ll partner closely with Product Managers, Engineering, and Design to uncover insights that improve the customer experience, drive engagement, and support long-term retention. You’ll play a key role in reinforcing CompanyCam’s continuous discovery approach by helping teams: - Define success metrics - Validate assumptions - Measure experimentation outcomes - Use data to guide product strategy This role blends analytical rigor, experimentation, and stakeholder collaboration in a fast-paced SaaS environment. Location: This is a remote position. You must live and work permanently in the U.S. to be considered. What You'll Do - Partner with Product Managers to define KPIs, measure success, and support continuous discovery practices - Analyze product usage, customer behavior, and funnel performance to identify trends and opportunities - Support experimentation and A/B testing efforts by measuring results and translating findings into actionable recommendations - Build and maintain dashboards and reporting in tools such as Metabase and Amplitude - Develop analyses that help teams improve product adoption, engagement, and retention - Work with cross-functional teams to ensure consistent metric definitions and trusted reporting - Leverage SQL, dbt, and analytics tools to transform and analyze product data - Enable self-service analytics by training stakeholders on dashboards, reporting tools, and best practices - Communicate complex findings clearly and effectively to both technical and non-technical audiences - Help foster a culture of experimentation, curiosity, and data-driven decision-making across Product and Engineering teams The Impact You'll Have At CompanyCam, your work makes a real impact. Whether you're writing code, supporting customers, or designing experiences, your contributions directly shape the product we deliver and the people we serve. In this role, you’ll drive impact by: - Helping product teams make more informed, customer-focused decisions - Improving product experiences through experimentation and behavioral insights - Increasing visibility into product performance, engagement, and retention trends - Strengthening the company’s culture of continuous discovery and data-driven iteration - Empowering teams with accessible, trusted analytics and reporting tools Qualifications - 2+ years of experience in product analytics, data analytics, or a related field - Strong SQL skills and experience working with modern analytics tools such as dbt, Metabase, Amplitude, Secoda, or similar platforms - Experience supporting product experimentation and A/B testing initiatives - Strong analytical and problem-solving skills with the ability to turn complex data into actionable insights - Experience building dashboards, reports, and data visualizations for business stakeholders - Ability to communicate findings clearly across technical and non-technical audiences - Comfortable working in a fast-paced, collaborative product environment - Experience working closely with Product and Engineering teams in a SaaS environment - Familiarity with cohort analysis, funnel optimization, and behavioral analytics - Background in statistics, experimentation methodology, or quantitative analysis - Passion for continuous learning, experimentation, and improving decision-making through data - A continuous growth-mindset, with a focus on learning, embracing challenges, and continuously improving - A knack for creativity and innovation, bringing fresh ideas to the table and solving complex problems Benefits - This is a salaried position at CompanyCam. Our starting salary range is $115,000-$123,000 per year and is based on experience. - We also offer meaningful equity and other benefits.

Role Description As a Senior Manager of Product Data Science, you will be a key leadership figure within the Product Data Science organisation, responsible for building and scaling a high-performing team of Analysts and Data Scientists embedded within Product domains. You will not only deliver impact through your team, but also raise the overall analytical and technical bar of the organisation, ensuring data science, experimentation, and product analytics are consistently applied at a high standard across multiple product areas. You will act as a force multiplier for decision-making quality, improving how Product, Engineering, Design, and Commercial teams use data to shape strategy, prioritise work, and evaluate impact. What You’ll Do - Lead, develop, and grow a team of Product Analysts and/or Data Scientists, ensuring consistently high performance, strong technical standards, and clear ownership of impact. - Drive effective goal-setting, planning and execution processes across Product Data Science, bringing leadership and discipline to OKRs, prioritisation and delivery against strategic objectives. - Set and continuously raise the bar for analytical quality, experimentation rigour, and data science application across your teams, ensuring outputs are robust, actionable, and decision-oriented. - Act as a senior technical and strategic leader, reviewing and shaping high-impact analytical work, experimentation design, and advanced modelling approaches where required. - Partner closely with senior Product, Engineering, Marketing, and Commercial leaders to define priorities, shape roadmaps, and ensure data science is embedded in strategic decision-making. - Translate ambiguous business problems into structured analytical and data science problems, ensuring your team delivers clear, commercially meaningful recommendations. - Drive adoption of scalable analytical frameworks, experimentation standards, and AI-enabled tooling to improve efficiency, consistency, and speed of decision-making across teams. - Champion best practices in experimentation, causal inference, segmentation, and customer understanding, ensuring statistical and analytical rigor across the organisation. - Build and maintain strong partnerships with Data Platform, Data Engineering and other central data functions, ensuring the team can effectively leverage shared capabilities while influencing the long-term data ecosystem. - Build and evolve the team’s capability through hiring, coaching, and performance management, ensuring strong technical depth and leadership within the function. - Identify and remove systemic blockers to high-quality analytics delivery, improving tooling, processes, ways of working and organisational effectiveness across Product Data Science while leading change that enables the team to scale. - Influence and align cross-functional stakeholders across multiple product domains, ensuring clarity, prioritisation, and strong decision-making discipline. Qualifications - Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization. - Expert Level proficiency in Python and SQL. - Deep, hands-on experience with statistical modeling, (quasi) experimentation, multi-arm bandit, and a wide range of machine learning techniques (e.g., Regression, Classification, Clustering). - Demonstrated ability to define, implement, and operationalise crucial product and feature-level metrics from scratch. - A proven track record of driving strategic impact through proactive and collaborative approach with the proven ability to lead technical discussions, drive product strategy, and communicate complex insights effectively to cross-functional partners (e.g., Product, Engineering, Design). - Experience scaling analytics or data science capabilities, driving impact through the creation of automated processes, self-service tools, or data products. - Leader in critical thinking, with previous experience demonstrating the analysis of available facts, evidence, observations, and arguments in order to form a judgment by the application of rational, skeptical, and unbiased analyses and evaluation. - Outstanding leadership skills, with experience in mentoring, coaching, and developing teams of analysts or data scientists. - Exceptional collaboration and communication skills, with the ability to engage, influence, and inspire cross-functional partners at all levels. - Proven ability to build strong relationships and drive outcomes across Product, Engineering, Data Platform and other central functions, often without direct authority. - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Requirements - Experience working within a high-scale technology company, marketplace, e-commerce business, or travel technology organisation. - A strong technical background in Product Data Science, Data Science, Experimentation, or Machine Learning before moving into leadership roles. - Experience building and scaling experimentation platforms, measurement frameworks, self-service capabilities, or data products. - Experience applying AI, Large Language Models (LLMs), Agentic AI, or automation technologies to improve analytics productivity and decision-making effectiveness. - Experience leading organisational change, improving analytical maturity, and raising standards across multiple teams or functions. - A reputation for raising the standard of thinking, execution, and decision-making in every team and organisation you join. Benefits