Data Science/Engineer & AI Coach / Assessor

Tyne & Wear
Boldon Colliery, UK
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
£60,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Information Engineering Extract Transform Load (ETL) Python (Programming Language) Machine Learning Cloud Services SQL Databases Snowflake Information Technology
+3 more
Machine Learning Operations Data Pipelines Databricks

Job description

funding. What you’ll do:As an Independent End Point Assessor, you will assess apprentices against the requirements of three technical standards and make robust, evidence-based grading decisions. You will:Conduct end point assessments across Data Engineer L5, Machine Learning Engineer L6 and AI Data Specialist L7, applying each assessment plan accurately.Assess project reports, presentations, professional discussions and technical tests, and grade to pass, merit or distinction against the published criteria.Question apprentices with enough technical depth to test genuine competence, not just surface knowledge.Give clear, fair and constructive feedback, and produce high-quality written assessment records.Maintain consistency and standardisation across assessments, contributing to standardisation activities and moderation.Keep up to date with changes to the standards and assessment plans. Technical experience required:This is a technical role. You will be assessing at Level 5 through Level

Requirements

7, so you need genuine hands-on depth across some or all of the following:Data engineering: building and maintaining data pipelines, ETL/ELT, SQL, cloud data platforms (for example Azure, AWS or GCP), tools such as dbt, Databricks, Airflow, Snowflake or BigQuery.Machine learning: designing, training, deploying and monitoring models in production, Python, and the ML lifecycle including MLOps.Applied AI: modern AI and generative AI techniques, responsible AI, and evaluating AI systems.Occupational competence at or above the level you are assessing, evidenced by your own career experience. Desirable qualifications and experience:Degree in a technical or numerate subject (data, computer science, engineering, maths or similar). A master’s is an advantage for Level 7.Assessor qualifications (A1, TAQA, CAVA, or D32/D33), or a willingness to work towards them.Familiarity with apprenticeship standards and end point assessment processes.Previous EPA, assessing, coaching or teaching experience in a technical setting.Experience using e-portfolio systems to capture evidence of learning. If this sounds like a good match, please get in touch ASAP as remote interviews are taking place immediately.

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