Staff Data Scientist

🏢 Summary: Lead an international multidisciplinary engineering team delivering and modernizing recruitment technology, including business-critical document-parsing systems and AI-driven solutions. The hybrid role combines people management, delivery ownership, and technical leadership across global product and engineering stakeholders. 🗂️ Requirements: 2+ years leading software engineers as an Engineering Manager, Software Development Manager, Technical Lead, or similar, Experience leading agile product engineering teams, Experience managing delivery, capacity, risks, and technical priorities, Experience mentoring engineers, managing performance, and supporting career growth, Previous hands-on software engineering experience, Strong knowledge of software architecture, APIs, CI/CD, cloud environments, and modern development practices, Understanding of machine learning and LLM-based product applications, Ability to assess architecture, technical debt, quality, scalability, and engineering trade-offs, Experience working in distributed international organizations, Practical experience using AI tools in engineering or management workflows, Fluent English 📃 Skills: Python, Perl, APIs, CI/CD, AWS, MachineLearning, DeepLearning, LLMs, GitHubCopilot, Claude, Gemini, ChatGPT 🏢 Description: We are hiring on behalf of our client, a global leader in HR technology, delivering an end-to-end SaaS platform that supports the entire recruitment lifecycle. Trusted by thousands of organizations worldwide, their solutions combine cloud technology, automation, and cutting-edge AI to help businesses hire smarter, work more efficiently, and deliver better talent experiences. We are looking for a Lead/Manager to lead an international team of Software Engineers, AI Engineers, and Data Analysts. This is primarily a people leadership and delivery role with a strong technical component . You will coach the team, drive predictable execution, partner with Product and Engineering leaders across Europe and North America, and help modernize a technology stack that combines legacy systems with AI-driven solutions. Key takeaways: Stack: Python, Machine Learning, Deep Learning, LLMs, APIs, CI/CD, AWS, leadership experience Salary: 23 000 PLN - 28 500 PLN gross on the Contract of Employment Working model: hybrid - 3x weekly from the office Location: Krakow Recruitment process: A call with Motife recruiter (30 min) Criteria Cognitive Aptitude Test (30 min) Hiring Manager Interview (30 min) Technical Interview (90 min) Responsibilities: Team Leadership Lead and support a multidisciplinary engineering team of up to 11 Software Engineers, AI Engineers, and Data Analysts. Coach team members through regular 1:1s, structured feedback, performance reviews, and individual development plans. Build a high-trust environment based on transparency, ownership, constructive feedback, and continuous development. Delivery & Engineering Excellence Own sprint execution, workload planning, delivery predictability, and proactive risk management. Partner with engineers and architects to maintain software quality, address technical debt, and improve engineering processes. Ensure the team balances new development with the stability and maintainability of business-critical parsing systems. Product & Global Collaboration Partner with Product Managers and Product Owners to refine priorities, assess technical complexity, and translate business needs into achievable engineering plans. Coordinate with engineering leaders and stakeholders across Europe and North America. Ensure engineering initiatives contribute directly to customer value and wider business objectives. AI & Technology Modernization Guide the evolution of document-processing technologies combining Perl, Python, machine learning, deep learning, and LLM-based approaches. Drive practical adoption of AI tools across engineering, testing, development, and team workflows. Identify opportunities to modernize legacy solutions without compromising reliability or operational performance. Requirements: Leadership Experience 2+ years of experience as an Engineering Manager, Software Development Manager, Technical Lead, or similar role with direct responsibility for software engineers. Proven experience leading agile product engineering teams and managing delivery, capacity, risks, and technical priorities. Strong track record of mentoring engineers, managing performance, and supporting career progression. Technical Expertise Previous hands-on software engineering experience and the technical depth required to effectively manage experienced engineers. Strong understanding of software architecture, APIs, CI/CD, cloud environments, and modern software development practices. Good understanding of machine learning and LLM-based technologies and how they can be applied within software products. Ability to discuss architecture, technical debt, software quality, scalability, and engineering trade-offs with senior technical stakeholders. Collaboration & Mindset Experience working in distributed, international organizations, ideally across European and North American time zones. Strong ownership mindset with the ability to communicate risks clearly and make pragmatic decisions. Practical experience using AI tools such as GitHub Copilot, Claude, Gemini, or ChatGPT within engineering or management workflows. Fluent English and strong written and verbal communication skills. What we offer: Medical care Life insurance Multisport Apply now If you combine strong people leadership with solid engineering judgment and an interest in practical AI adoption, we’d like to hear from you! Apply via our careers page and please submit your CV in English.

🏢 Summary: Lead the data science strategy and production delivery for an advertising marketplace across onsite and offsite channels. The role manages scientists building ranking, bidding, budget, ROAS, and GenAI systems while partnering with Product and Engineering to improve shopper relevance, advertiser outcomes, and revenue. 🗂️ Requirements: Advanced quantitative degree or 10+ years leading large-scale ML/optimization systems, Leadership of data science or applied science teams, End-to-end production science delivery experience, Large-scale ranking and prediction ML expertise, Advertising supply- and demand-side optimization experience, Production LLM or generative AI implementation experience, Mathematics, statistics, causal measurement, and experimentation expertise, Distributed training and serving pipeline experience, Senior executive and cross-functional communication skills 📃 Skills: MachineLearning, DeepLearning, Embeddings, Retrieval, Ranking, Optimization, Experimentation, MLOps, Auctions, Bidding, Pacing, ROAS, LLMs, GenAI, RAG, Statistics, CausalInference, AWS, SageMaker 🏢 Description: Your Opportunity Lead all Ads Data Science across onsite and offsite advertising channels, with accountability for science strategy and production implementation. Lead a team building the intelligence layer for the advertising marketplace across: - Supply-side algorithms: search, relevance, ranking, real-time bidding, bid boosting, premium positioning, and dynamic auctions. - Demand-side algorithms: budgeting, pacing, budget allocation and reallocation, keyword recommendations, bid recommendations, campaign setup and auto-optimization, and advertiser ROAS optimization. - Portfolio management: orchestration of onsite and offsite advertising portfolios to balance shopper experience, advertiser outcomes, and revenue. Define how modern AI, including LLMs, generative AI, foundation models, and multimodal systems, is deployed as durable production systems. Partner with Product, Engineering, and business stakeholders, and represent Ads science to senior leadership. What You’ll Own - Own Ads Data Science across onsite and offsite channels, including strategy, roadmap, model portfolio, delivery, and scientific quality. - Lead, grow, and mentor data scientists; establish standards for modeling, experimentation, MLOps, and research-to-production execution. - Advance applied science in embeddings, representation learning, CTR/CVR prediction, multi-objective ranking, auction and bidding dynamics, budget optimization, ROAS optimization, causal measurement, and marketplace balance. - Define and execute AI and GenAI workstreams, including generative creative and offer assistance, keyword and query recommendations, bid recommendations, automated bidding guidance, campaign setup and optimization copilots, and retrieval-augmented systems for relevance, discovery, and ranking. - Partner with Product and Engineering to deliver production systems that improve shopper relevance, advertiser ROI/ROAS, and advertising performance. - Establish experimentation and decision frameworks linking science investments to customer and revenue impact. - Communicate science strategy, tradeoffs, and recommendations to senior leadership. - Raise external scientific presence through publications, talks, and recruiting at ML, AI, and advertising venues. This is encouraged, not required. What You’ll Need - Advanced degree (M.S., PhD, or equivalent experience) in a quantitative field such as computer science, machine learning, statistics, operations research, applied mathematics, or data science; or 10+ years building and leading large-scale ML/optimization systems. - Experience leading data scientists or applied scientists and owning end-to-end production science delivery, ideally in advertising, search, recommendations, personalization, or marketplace systems. - Hands-on expertise in large-scale ranking and prediction ML, including deep learning, embeddings, retrieval, multi-objective optimization, and online experimentation. - Experience with advertising optimization systems across supply and demand, including auctions, real-time bidding, pacing, budget allocation, keyword and bid recommendations, auto-campaign optimization, and ROAS optimization in real-time constrained-spend environments. - Experience productizing LLMs or generative AI in real systems, such as RAG, agentic workflows, evaluation harnesses, and quality and safety controls; ideally in advertising, search, or ecommerce. - Strong mathematics, statistics, and scientific-method foundation, with high standards for model quality, causal measurement, and production reliability. - Experience operating distributed training and serving pipelines and partnering with Engineering on scalable deployment. - Ability to influence senior executives and cross-functional partners with clear, technically credible communication. Nice to Have - Digital advertising, retail media, or sponsored products experience. - Ecommerce or retail marketplace experience. - Cloud ML platform experience, such as AWS SageMaker or equivalent, and modern GenAI tooling. - Track record of hiring and developing senior scientific talent. What You’ll Get - Base salary range: $198,500–$300,000. Specific salary depends on relevant experience, education, and work location. - Eligibility for 401(k), new-hire and annual equity grants, and potentially an annual bonus for eligible positions. - Medical/Rx, vision, dental, life, disability, hospital indemnity, critical illness, and accident insurance. - Parental leave, family-services benefits, backup dependent care, flexible spending accounts, telemedicine, pet-adoption reimbursement, employee assistance services, and employee discounts. - Unlimited PTO for exempt salary team members, subject to manager approval, plus six paid holidays annually. Paid sick and family leave may be available in accordance with applicable state and local regulations.

🏢 Summary: Join a cross-functional product team to build and operate scalable, high-throughput Java backend solutions for eCommerce core processes. The role combines hands-on architecture, quality ownership and product discovery, with daily use of AI-assisted and agentic coding workflows. 🗂️ Requirements: Java 21+ backend experience, Reactive or asynchronous programming experience, Virtual threads experience, Distributed backend systems experience, Event-driven messaging experience, CI/CD and automated testing experience, Code review and observability experience, AI coding tools and agentic workflow experience, Product-oriented cross-functional collaboration 📃 Skills: Java, Vert.x, Reactor, Kafka, CI/CD, DDD, SOLID, Claude, Copilot, Scrum, Kanban 🏢 Description: We are one of Switzerland's leading online shops in both B2C and B2B - a combination that is nearly unique in Europe. Behind it stands one of the most modern logistics operations on the continent: highly automated, scalable and with further growth potential. Here you do more than build software. You bring your personality, actively shape the department and help define the eCommerce of tomorrow. The role Join a cross-functional product team and build scalable solutions with real impact for our customers and core business processes. You bring curiosity, team spirit and a genuine appetite for learning - and you take part in shaping not just the implementation, but the architecture, quality standards and the question of what should be built in the first place. What to expect A collaborative cross-functional product team with a hands-on Team Lead, a Product Manager and several T-shaped Full-Stack Engineers who share ownership together. You work in Scrum or Kanban depending on what fits the team. Engineers roll up their sleeves in refinement and actively contribute to architecture and product decisions - not just implementation. Plenty of room to shape high code quality within your team and across team boundaries. Enough legacy, complexity and grown structures to give you real opportunities to make things meaningfully better - one step at a time. What you bring We are a good match if you: Java & Backend Depth Bring deep, hands-on experience with Java 21+ - including modern language features such as records, sealed classes, pattern matching and structured concurrency Have practical experience with reactive or asynchronous programming models - with Vert.x, Project Reactor or comparable toolkits; you understand the non-blocking programming model and know when to apply it Have worked with Java virtual threads (Project Loom) and understand how they change concurrency models in practice - not just in theory Have built and operated distributed backend systems at scale - ideally in eCommerce or comparable high-throughput domains Are comfortable with event-driven communication patterns (Kafka, messaging systems) and understand the trade-offs between synchronous and asynchronous approaches Engineering Practices Have lived modern engineering practices in your daily work: CI/CD, automated testing, decoupling, code reviews and observability See concepts like DDD, Clean Architecture, Event-Driven Architecture, SOLID, feature flags and dependency injection as practical tools - not buzzwords - and apply them with pragmatism and judgement Are a strong advocate of "you build it, you own it" and have experience in environments that release multiple times per day Guide the team on code quality and meaningful testing practices - not coverage as a goal in itself, but tests that catch real bugs AI / Agentic Coding - a core expectation, not a nice-to-have Use AI coding tools - such as Claude Code or GitHub Copilot - as a natural part of your daily workflow for code generation, test writing, refactoring and documentation Go beyond autocomplete: you actively explore agentic workflows such as automated PR review, scaffolding, and multi-step code generation - and you evaluate their output critically before committing Understand the risks: you know that AI-generated code can accelerate technical debt and erode understanding if not reviewed carefully, and you enforce review standards accordingly Help introduce and shape AI tooling adoption within the team - sharing what works, what does not and where the limits are Collaboration & Product Mindset Enjoy sharing knowledge through pair programming, whiteboard sessions and code reviews - and actively help raise the engineering level of the team Like working closely with Product Managers and genuinely want to understand the problem being solved - you help shape requirements and think from a user and business perspective Value real agility: short iterations, fast learning, active feedback loops and data-informed decisions Are a warm communicator who values an open learning culture, builds personal connections within the team and does not take themselves too seriously We are probably not a good match if you: Prefer frameworks like SAFe or projects that start with a fixed requirements document Have worked primarily in heavily regulated environments without experience in a fast-moving, product-oriented setup with distributed systems Are most comfortable in models where infrastructure, backend, frontend, testing and product thinking are kept strictly separate Prefer to receive requirements fully formed rather than shaping them together with Product Management See AI tools as a threat or a gimmick rather than a genuine productivity multiplier worth mastering See ongoing learning primarily as the employer's responsibility rather than your own intrinsic motivation Are more frustrated than energised by imperfect systems - spoiler: we are not there yet Keep work and good humour strictly apart

🏢 Summary: Senior Associate role supporting regulated laboratory informatics systems from requirements gathering through testing, validation, deployment, and post-implementation support. The position partners with laboratory, operations, quality, and technical stakeholders to deliver compliant, fit-for-purpose solutions in a hybrid work arrangement. 🗂️ Requirements: MS/MA in a science-related discipline with 1+ years of industry experience, or BS/BA with 3+ years of industry experience, Understanding of solution development lifecycle activities in a regulated or quality-driven environment, Written and verbal communication skills, Organization skills to manage multiple priorities, timelines, and stakeholders, Microsoft Office 365 proficiency, Authorization for permanent employment in the United States, Availability for occasional evening and weekend work 📃 Skills: SDLC, cGLP, Validation, UAT, Microsoft365, LIMS, LabWare, SAS, SQL, ChatGPT, Copilot 🏢 Description: Use Your Power for Purpose In a world driven by rapid knowledge creation and supported by advanced technology platforms, the digital and data-first strategy aims to accelerate the development of impactful technology solutions for research, development, and medical functions. The team maintains systems and information security while supporting healthcare solutions through information technology. Your expertise in informatics will advance R&D by developing, supporting, and validating computer systems. You will generate high-quality assay data within a regulated cGLP (current Good Laboratory Practice) laboratory environment, support research initiatives, streamline processes, and ensure regulatory compliance for Research Department software solutions. What You Will Achieve As a Senior Associate, you will translate business needs from laboratory and operations teams into practical information-system solutions. You will partner with functional assay leads, operations leads, laboratory SMEs, and informatics partners to define requirements, support solution design, coordinate user testing, and manage project activities across the solution development lifecycle (SDLC). Your work will help ensure that information systems supporting regulated laboratory processes are fit for purpose, properly tested, and supported by appropriate documentation for validated environments. How You Will Achieve It - Partner with functional assay leads, operations leads, laboratory SMEs, and informatics partners to understand business needs and translate them into information-system solutions. - Elicit, document, and maintain business and end-user requirements for new solutions and enhancements to existing solutions. - Support solution design discussions by ensuring proposed system functionality aligns with laboratory workflows, operational needs, compliance expectations, and end-user requirements. - Project manage assigned system initiatives through the solution development lifecycle, including requirements gathering, design review, testing, validation readiness, deployment support, and post-implementation follow-up. - Develop, review, and execute user acceptance testing activities to confirm system functionality meets approved business and end-user requirements. - Guide end users through testing activities, support test execution, document results, capture defects, and coordinate issue resolution with technical teams. - Generate, review, and maintain documentation supporting validated systems, including requirements, test scripts, SOPs, change controls, and related project deliverables. - Facilitate regular project meetings with business stakeholders and technical partners to review priorities, status, risks, decisions, and action items. - Collaborate with quality, validation, laboratory, and technical teams to ensure system deliverables align with regulated-system expectations. - Maintain strict compliance with departmental, site, and corporate training, quality, and safety requirements. Here Is What You Need (Minimum Requirements) - MS/MA in a science-related discipline, such as computer science, mathematics, or biological science, with 1+ years of hands-on industry experience; or BS/BA with 3+ years of hands-on industry experience. - Understanding of solution development lifecycle activities in a regulated or quality-driven environment. - Strong written and verbal communication skills. - Strong organizational skills and the ability to manage multiple priorities, timelines, and stakeholders. - Proficiency in Microsoft Office 365 applications. Bonus Points If You Have (Preferred Requirements) - Experience supporting validated systems in a pharmaceutical, biotech, laboratory, or regulated environment. - Familiarity with laboratory informatics systems such as LabWare LIMS and statistical analysis applications such as SAS. - Experience creating documentation such as requirements, test scripts, traceability matrices, SOPs, or user guides. - Experience working with cross-functional teams across business, quality, and technical organizations. - Working knowledge of SQL and a basic understanding of computer programming languages. - Experience using common AI tools, including generative technologies such as ChatGPT or Microsoft Copilot, to support problem solving and productivity; curiosity about improving outcomes with these tools; and an understanding of responsible AI practices, including risk management and ethical use. Non-standard Work Schedule, Travel Or Environment Requirements - Occasional evening and weekend work to meet critical deliverables. - Work location assignment: Hybrid. Compensation and Benefits The annual base salary range is $82,700.00 to $137,900.00. The position is eligible for participation in the Global Performance Plan with a bonus target of 10.0% of base salary. Benefits include a 401(k) plan with matching contributions and an additional retirement savings contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and medical, prescription drug, dental, and vision coverage. Compensation structures and benefit packages are aligned based on the location of hire. The United States salary range does not apply to Tampa, FL, or locations outside the United States. Relocation assistance may be available based on business needs and/or eligibility. Work Authorization Candidates must be authorized to be employed in the U.S. by any employer. U.S. work visa sponsorship, including TN, O-1, and H-1B, is not available now or in the future. Sunshine Act Payments and other transfers of value to health care providers are reported as required by federal and state transparency laws and implementing regulations. Subject to legal review and statutory or regulatory clarification, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. If recruiting expenses resulting from an interview are paid or reimbursed for a licensed physician, the physician’s name, address, and amount of payments made may be reported to the government. EEO & Employment Eligibility Equal employment opportunity applies to all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or expression, national origin, disability, or veteran status. The position requires permanent work authorization in the United States. Employment eligibility verification requirements apply.