Sr. Machine learning /Data Scientist

Job description

Company Description Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of what we do: UK & Ireland's premier AWS, Microsoft & Oracle partner 3300+ strong, €350/£300m revenue business 10+ years as a Great Place to Work in Ireland & UK Best Workplace for Women in the UK & Ireland by GPTW Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you. Job Description Role Overview We are seeking a Data Scientist to who combines strong machine learning fundamentals with the ability to build high‑quality, production-ready software. You’ll take ML solutions from problem framing and modelling through to robust implementation, deployment, and iteration, working closely with engineers and stakeholders to deliver measurable outcomes for enterprise and regulated clients. The role suits someone focused on real world delivery and measurable outcomes, rather than research in isolation. Key Responsibilities · Design, build, and deploy machine learning solutions that solve real business problems, moving from prototype to production. Apply traditional ML (e.g., regression/classification/clustering) and deep learning techniques where appropriate, selecting models based on evidence and constraints. Demonstrate strong ML fundamentals, including the mathematics behind models (probability, statistics, optimisation, linear algebra), and explain trade-offs clearly. Develop and deploy ML and data science solutions from proof of concept to production Perform data exploration, feature engineering, and model development on large datasets Track experiments, metrics, and model versions (e.g. MLflow) Collaborate with data engineers and AI engineers to integrate models into platforms Continuously improve models based on performance, feedback, and data drift Qualifications Required Skills & Experience 5+ years in applied machine learning and deep learning roles Strong grounding in core ML concepts and their mathematical basis: Probability & statistics, hypothesis testing, bias/variance, regularisation Optimisation (e.g., gradient-based methods), loss functions, evaluation metrics Linear algebra fundamentals used in ML (vectors/matrices, decompositions at a practical level) Solid practical experience with traditional ML modelling (feature engineering, model selection, validation, and error analysis). Demonstrable exposure to deep learning (architectures, training dynamics, evaluation), beyond “surface-level” familiarity. Proven ability to build good quality software, not just models—clean code, testing, debugging, and maintainable design. Strong programming skills (typically Python; additional languages a plus) and experience integrating ML into production systems. A clear problem-solving mindset: structured thought process, ability to reason through ambiguous requirements, and iterate effectively. Hands-on experience delivering ML solutions end-to-end, including prototyping, validation, and production/operations. Experience with Databricks and Spark Hands-on use of MLflow or similar model lifecycle and MLOps frameworks Experience with deep learning frameworks (e.g. PyTorch) Practical experience with GenAI / LLMs Exposure to AWS Bedrock & AWS SageMaker Strong SQL and data analysis skills Nice to Have Experience in regulated or security conscious environments Familiarity with model governance, monitoring, and managing model performance over time. Exposure to production model deployment patterns Familiarity with Responsible AI and model governance Client facing or consulting experience Additional Information Why Version 1? At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability. Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat Reward schemes including Version 1’s Annual Excellence Awards & ‘Call-Out’ platform. Environment, Social and Community First initiatives allow you to get involved in local fundraising and development opportunities as part of fostering our diversity, inclusion and belonging schemes. And many more exciting benefits… drop us a note to find out more. Version 1 is an equal opportunities employer. We are committed to building a diverse, inclusive and respectful workplace where everyone feels valued and able to thrive. We welcome applications from people of all backgrounds, identities and lived experiences, and we value the different perspectives people bring. We want every candidate to have a positive and accessible recruitment experience. If you need reasonable adjustments at any stage of the process, please contact [recruiter email address][EM1] at Version 1. We will consider all requests carefully, respectfully and confidentially. Video links: https://www.youtube.com/watch?v=F_d3ELTH5zo [EM1]Please add the email address for the lead recruiter