Data Science Consultant Trainers

TrainingCred Institute is seeking experienced Data Scientists to design and deliver practical, engaging training programmes in data science, statistical analysis and machine learning.We welcome practitioners and consultants who combine hands-on experience solving real-world data problems with the ability to help professionals build and apply technical skills. You will work with our training team to understand client needs, customise course materials and facilitate learning through coding exercises, case studies and applied projects.Successful candidates will demonstrate strong technical expertise, clear communication and a commitment to helping participants turn data into useful insights and reliable analytical solutions.Areas of SpecialisationApplicants should demonstrate expertise in one or more of the following areas:Python or R for data science.SQL, data extraction and database querying.Data cleaning, preparation and exploratory data analysis.Statistics, hypothesis testing and experimental design.Machine learning, predictive modelling and model evaluation.Time series analysis and forecasting.Natural language processing and text analytics.Deep learning and computer vision.Generative AI and applied large language models.Data visualisation and communication of analytical findings.Data pipelines, model deployment and MLOps.Responsible AI, model explainability and data privacy.Applicants should identify the specific topics, tools and participant levels they are qualified to teach. Expertise in every area is not required.Key ResponsibilitiesAssess training needs. Establish participants’ technical backgrounds, workplace challenges and learning objectives, and identify suitable prerequisites for each programme.Develop practical training materials. Prepare course outlines, session plans, presentations, notebooks, datasets, coding exercises, assessments and participant resources.Deliver engaging training. Facilitate classroom, virtual and client-site sessions using demonstrations, guided coding, discussions and hands-on projects.Teach the data science workflow. Guide participants through problem definition, data preparation, exploration, modelling, evaluation and communication of results.Build sound analytical judgement. Help participants recognise issues such as data leakage, sampling bias, overfitting and inappropriate evaluation metrics.Connect learning to workplace needs. Use relevant case studies to show how data science supports operational, business and programme decisions.Support practical exercises. Help participants troubleshoot code, interpret results and understand the assumptions and limitations of their analyses.Assess participant progress. Use exercises, project reviews and feedback to evaluate learning and address gaps in understanding.Maintain relevant content. Update materials to reflect developments in data science tools, methods and professional practice.Coordinate delivery. Submit materials on time, confirm software and computing requirements, and collaborate with the team on training logistics.Report outcomes. Provide agreed training reports, review participant feedback and recommend improvements.Uphold professional standards. Protect confidential information, use appropriately licensed or anonymised datasets, and maintain an inclusive learning environment.Qualifications and Professional ExperienceA master’s degree in Data Science, Statistics, Computer Science, Mathematics, Engineering or a closely related quantitative discipline.At least three years of relevant professional experience in data science, machine learning or applied statistical analysis.Demonstrated experience delivering training, facilitating technical workshops or teaching specialist content to professional audiences.Practical experience working with real-world datasets and developing analytical or machine learning solutions.Proficiency in Python or R, together with SQL and relevant data science libraries.Strong understanding of statistical methods, model validation and the interpretation of analytical results.Ability to explain complex concepts clearly and adapt technical content to participants with different levels of experience.Excellent presentation, written communication and interpersonal skills.Familiarity with adult learning principles and tools for effective virtual facilitation.A dependable approach to preparation, deadlines and collaboration.Relevant professional certifications, recognised trainer qualifications, and experience deploying or monitoring models are added advantages.Why Work with TrainingCred?Apply your expertise to practical learning programmes that address real organisational challenges.Work with professionals from different sectors, organisations and technical backgrounds.Contribute to course development while our team coordinates programme delivery, participant communication and logistics.Method of ApplicationSend your application to trainers@trainingcred.com and include:Your current CV, including your telephone number, email address and location.A brief cover letter describing your data science expertise, industry experience and training background.A list of the courses or topics you can deliver, including relevant tools and the participant levels you can support.Contact details for three professional referees who can comment on your technical expertise or training experience.Your availability for classroom and virtual assignments, and willingness to travel where required.Where available, a link to a training portfolio, public code repository, sample course outline or non-confidential project demonstrating your work.