Staff Data Scientist

🏢 Summary: Senior Data Scientist role focused on building and operating real-time, AI-driven decisioning systems that directly impact user experience and conversion rates. The position involves developing and deploying production-grade machine learning models with strict low-latency requirements and contributing to personalization, experimentation, and recommendation systems. It combines hands-on ML engineering with experimentation, causal analysis, and large-scale data processing in a business-facing environment. 🗂️ Requirements: 7+ years commercial experience in Data Science with production ML focus, Strong experience deploying and maintaining production ML models, Experience with real-time systems and low-latency constraints, Proficiency in Python and SQL, Hands-on experience with gradient boosting methods, Experience with recommendation systems and uplift modeling, Strong knowledge of A/B testing and causal inference, Experience building feature engineering pipelines at scale, Experience with Apache Spark or PySpark, Cloud platform experience (AWS preferred), Familiarity with LLMs and GenAI for personalization 📃 Skills: Python, SQL, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, PySpark, Spark, AWS, Databricks, NLP, LLM, GenAI 🏢 Description: We are looking for a Senior Data Scientist to join a Growth Alliance team focused on AI-driven decisioning and user-facing machine learning systems. This role is suited for a technically strong data scientist who is equally comfortable working with business stakeholders and operating production ML systems at scale. About the Project: This is a high-impact role working directly on systems that influence end-user experience and conversion. You will operate in a real-time environment with strict low-latency requirements (<40 ms), contributing to a shift toward AI-driven decisioning aimed at improving product performance and increasing conversion rates. The work spans production ML pipelines, experimentation, and personalization, not just research or experimentation in isolation. Responsibilities: Design, develop, and deploy production machine learning models with real-time constraints; Build and maintain recommendation systems, uplift models, and contextual bandit frameworks; Conduct A/B testing, causal inference analyses, and statistical hypothesis testing; Develop and maintain feature engineering pipelines at scale using PySpark / Apache Spark; Monitor and validate deployed models to ensure performance and reliability; Collaborate closely with business stakeholders to challenge assumptions and define the right problems; Contribute to generative AI and LLM-based personalization initiatives; Work with decisioning platforms, personalization engines, and Martech integrations. Qualifications: 7+ years of commercial experience in Data Science with a strong production ML focus; Proficiency in Python (NumPy, Pandas, Scikit-learn) and SQL; Hands-on experience with gradient boosting methods (XGBoost, LightGBM); Experience with recommendation systems, clustering, NLP, and uplift modeling; Solid background in A/B testing frameworks, causal inference, and statistical modeling; Experience with feature engineering and production ML pipelines at scale; Cloud platform experience, preferably AWS; Familiarity with LLMs, prompt engineering, and GenAI for content personalization; Strong communication skills and ability to work in a highly business-facing environment; Databricks experience is a nice to have. Recruitment Process: Initial interview with our recruitment team; Interview with the hiring manager; Live Coding Assessment; Meeting with the Project Manager. Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.

🏢 Summary: Senior Data Scientist role focused on leading the design and delivery of production-grade Generative AI solutions using LLMs, including RAG pipelines, chatbots, and AI agents. The position combines hands-on development with architectural decision-making and technical mentorship, delivering scalable GenAI systems for large enterprise clients. You will own the full lifecycle from solution discovery through deployment, safety, and optimization. 🗂️ Requirements: 6+ years experience in Data Science or AI engineering, 4+ years production experience with Python for AI/ML, 2+ years building and deploying LLM-based systems in production, Experience designing and implementing RAG pipelines, Experience with model fine-tuning techniques (LoRA, QLoRA, SFT), Experience building end-to-end GenAI applications including orchestration and APIs, Ability to design system architectures for LLM-based solutions, Experience implementing AI safety and governance controls, Strong analytical and problem-solving skills, Professional English communication skills 📃 Skills: Python, LLMs, LangChain, LlamaIndex, LangGraph, RAG, LoRA, QLoRA, SFT, APIs, VectorDB, AI, MachineLearning 🏢 Description: ABOUT THE COMPANY Our client is an end-to-end data services partner to global enterprises, founded in 2008 and headquartered in Warsaw. Our teams work with over 75 leading consumer packaged goods brands across more than 30 countries, helping them unlock the full value of their data — from strategy and development through to operations and adoption. Our work spans supply chain analytics, customer analytics, AI and machine learning, data platforms, and digital commerce. We are recognised as a Strong Performer in the Gartner Peer Insights Voice of the Customer report for data and analytics, and hold Great Place to Work certification in multiple countries. ABOUT THE ROLE We're looking for an experienced Senior Data Scientist with deep expertise in Generative AI to lead projects building and implementing advanced LLM-based systems — including chatbots, AI agents, and RAG pipelines. This is a technical leadership role: you'll make architectural decisions, select technologies, set best practices, and mentor other engineers, while remaining hands-on across the full solution lifecycle. You'll work closely with data engineers, product owners, and full-stack developers to deliver scalable GenAI applications for large enterprise clients, primarily in CPG, retail, and manufacturing. WHAT YOU'LL WORK ON Solution design and discovery Lead discovery and solution design for GenAI use cases — translating business problems into concrete architectures covering LLM selection, RAG, fine-tuning, agents, and guardrails. End-to-end GenAI applications Build complete GenAI solutions covering data ingestion, retrieval layers, orchestration (LangChain, LlamaIndex, LangGraph), API and backend, and lightweight UI where needed. RAG pipeline design Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness. Model selection, prompting, and fine-tuning Own prompting strategies, model selection, and fine-tuning (LoRA, QLoRA, SFT) for text, code, and multimodal models, including evaluation and A/B testing. Safety and governance Implement safety, compliance, and governance controls including input/output filters, PII handling, audit logs, and human-in-the-loop review where required. Requirements and estimation Gather technical requirements from stakeholders and produce reliable estimates for planned work. Mentorship and knowledge sharing Mentor other data scientists and engineers in GenAI patterns, code quality, and best practices. Contribute to internal libraries, templates, and reusable components. Staying current Track the GenAI landscape — new open and hosted models, agentic frameworks, evaluation techniques — and run targeted PoCs to validate emerging approaches. WHAT WE LOOK FOR 6+ years in Data Science or AI engineering Broad experience across the data science and AI stack, with a track record of delivering production systems. 4+ years of production Python for AI Fluent in writing production-ready Python for AI and ML workloads — clean, maintainable, and deployable. 2+ years of production LLM development Hands-on experience building and shipping LLM-based systems in production environments, not just research or prototypes. Strong analytical and problem-solving skills Able to break down ambiguous problems, make sound architectural decisions under uncertainty, and defend those decisions clearly. Excellent English communication Comfortable working directly with international clients and cross-functional teams. Able to translate technical complexity for non-technical stakeholders. THE TEAM You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates. COMPENSATION & BENEFITS Rate 105 – 170 PLN per hour on a B2B contract, depending on experience. Work model Fully remote or office-based — your choice. Flexibility on working hours and contract form. Workation policy Option to work remotely from other locations for defined periods. Onboarding Comprehensive online onboarding programme with a dedicated buddy from day one. Learning and development Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year. Career growth Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation. Referral bonuses Financial rewards for successful employee referrals. Wellbeing Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives. Equipment Modern office equipment provided. Employer recognition Great Place to Work certified employer.

🏢 Summary: Lead Data Engineer role focused on building scalable AI and cloud-based data solutions in a global environment. The position involves leading data engineering initiatives, designing secure cloud architectures, and supporting AI applications using AWS or Azure. The offer includes hybrid work, professional development opportunities, and a comprehensive benefits package. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python, Experience designing and scaling complex data systems, Hands-on experience with AI technologies, Experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs, data integration, automation tools, and data governance, Understanding of data security and compliance standards, Leadership and mentoring experience, English and Polish proficiency (minimum B2) 📃 Skills: Python, SQL, AWS, Azure, Java, APIs, DevOps, AI, RAG, MCP, Automation, DataGovernance 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Lead Data Engineer role focused on driving AI initiatives and building scalable cloud-based data architectures in a global environment. The position involves technical ownership of data platforms, designing secure and high-performing systems, and leading data engineering efforts in a DevOps setting. The role emphasizes AI integration, cloud infrastructure, and enterprise-grade data governance. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python in production, Strong experience designing and scaling complex data systems, Hands-on experience with AI technologies, Hands-on experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs and data integration, Experience with automation tools, Knowledge of data governance practices, Understanding of data security and compliance standards, Proven experience leading and mentoring engineers 📃 Skills: Python, SQL, AWS, Azure, Java, AI, RAG, MCP, APIs, DevOps, Automation, Monitoring, Cloud, DataEngineering, DataPipelines, Governance, Security, Compliance, Backend 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Remote AI Lead Data Engineer role responsible for designing and delivering enterprise-grade AI data platforms while leading a team of engineers. The position focuses on building scalable Lakehouse architectures, advanced MLOps frameworks, and LLM orchestration pipelines. It bridges Data Science and Data Engineering to ensure robust, governed, and production-ready AI infrastructure. 🗂️ Requirements: 8–10 years of Data Engineering experience, Minimum 3 years in technical lead role, Expert-level Python, Expert-level SQL, Expert-level PySpark in distributed environments, Experience with SageMaker, Azure ML, or Vertex AI, Hands-on MLflow or Kubeflow for CI/CD, Experience with Monte Carlo or Datadog, Experience with Collibra or Alation, Implementation of Responsible AI guardrails, Knowledge of Medallion, Data Mesh, Lakehouse architectures, Experience with PII masking and data lineage, Knowledge of HIPAA and GDPR compliance 📃 Skills: Python, SQL, PySpark, SageMaker, AzureML, VertexAI, MLflow, Kubeflow, MonteCarlo, Datadog, Collibra, Alation, Lakehouse, Medallion, DataMesh, CI/CD, LLM, HIPAA, GDPR 🏢 Description: This is a remote position. The AI Lead Data Engineer acts as the technical lighthouse for our data squads. With 8–10 years of experience, you are responsible for the technical design and delivery of robust AI data platforms. You will bridge the gap between Data Science and Data Engineering, ensuring that our infrastructure supports advanced MLOps and LLM requirements while leading a team of engineers to maintain elite coding and governance standards. Key Responsibilities: Technical Leadership: Lead a squad of data engineers in the design and execution of end-to-end AI data architectures. AI Observability & Governance: Build frameworks for bias detection, ethical AI considerations, and auditability using platforms like Collibra or Alation. Infrastructure Design: Lead the transition to Data Lakehouse architectures and implement feature stores for enterprise-wide model reuse. Delivery Management: Work with stakeholders to manage project milestones, technical risks, and on-time delivery. Advanced MLOps: Implement enterprise-grade CI/CD for ML workflows using MLflow or Kubeflow. GenAI Orchestration: Design specialized pipelines for LLM evaluation frameworks and prompt-tuning datasets. Requirements 8–10 years of experience with at least 3 years in a lead role managing technical delivery. Expert-level Python, SQL, and PySpark optimization for distributed environments. Deep experience with AI platform services such as Amazon SageMaker, Azure ML, or Vertex AI. Hands-on experience implementing enterprise observability with Monte Carlo or Datadog. Experience with data governance platforms (Collibra/Alation) and implementing Responsible AI guardrails. Deep understanding of modern data patterns (Medallion architecture, Data Mesh, Lakehouse). Advanced knowledge of security frameworks, including PII masking, data lineage, and HIPAA/GDPR compliance. Exceptional ability to mentor junior engineers and communicate complex data strategies to business stakeholders. Benefits Professional training programs Work with a team that’s recognized for its excellence. We’ve been featured in the Deloitte Technology Fast 50 & FT 1000 rankings. We’ve also received the Great Place To Work® certification for five years in a row