Data Science Team Lead

Data Science Team Lead Location: [Prague, hybrid] / [South Africa, remote] About the Role We are looking for a Data Science Team Lead to lead and grow the data science team behind our machine-learning-based SaaS product for the mining industry. This is a dual role combining technical leadership with people management. You will set the technical direction for how we build and ship ML solutions, and you will directly manage, coach, and hire the data scientists on your team. Responsibilities Technical leadership & architecture Lead the design and implementation of ML production pipelines and the data science team's tooling. Own the technical feasibility of data science solutions across the product. Drive adoption of new analytical techniques and technologies. Set coding and modeling standards and oversee overall code and model quality. Team leadership & people management Manage a team of data scientists, holding regular 1-1s and being their first point of support. Set individual goals, give continuous feedback, and run performance reviews. Coach team members and help them develop their careers, skills, and autonomy. Build a healthy, collaborative, and psychologically safe team culture, and own team engagement and retention. Hiring & team building Own hiring for the data science team: define the roles needed together with the Head of Engineering, and interview candidates to assess technical and behavioral fit. Make hiring decisions in partnership with the Head of Engineering and recruitment. Onboard new team members. Delivery & project oversight Plan and deliver data science projects aligned with business goals. Manage project risks, estimates, dependencies, and stakeholder communication. Balance research and experimentation with reliable, predictable delivery of customer projects. Innovation & thought leadership Communicate ML solutions and research findings across the company. Support go-to-market efforts by explaining data science solutions to prospects and clients. Represent the company externally through conference talks or technical publications. Requirements 6+ years in data science, including 1+ years leading a team. Hands-on experience building, deploying, and running ML models in production (MLOps). Strong Python skills and experience with ML frameworks such as scikit-learn, xgboost or tensorflow. Solid grounding in statistics, optimization, and current ML methods. Experience managing, hiring, and coaching data scientists — 1-1s, feedback, performance, and career growth. Able to turn business problems into data science solutions and explain them clearly to non-technical colleagues. Strong communication and teamwork; comfortable in an agile environment. Bachelor's degree in a quantitative field (e.g. Computer Science, Statistics, Mathematics, Physics); Master's or PhD a plus. Nice to haves Experience with cloud platforms (Google Cloud, AWS, or Azure). Experience with big data technologies and tools (e.g. Spark). Background in mining, process engineering, or another industrial domain. Publications, conference talks, or open-source contributions in ML / data science. Experience supporting go-to-market or presenting solutions to clients.