Part Time Machine Learning Analyst - Machine Learning Specialist - Machine Learning Research Associate Jobs, in Lean Six Sigma Processes - Maukerja

Role Description

Apply machine learning and analytical methods to solve business or research problems. Prepare reliable datasets, develop and evaluate models, and communicate findings clearly, with implementation and research responsibilities appropriate to the assigned role.

Key Responsibilities

• Translate business or research questions into analytical objectives and evaluation criteria.
• Gather, clean, explore, and validate data from approved sources.
• Assess data quality, representativeness, permitted use, and potential bias.
• Develop features, establish baselines, and select suitable modelling approaches.
• Train and evaluate models using appropriate validation methods and safeguards against data leakage.
• Analyze errors, robustness, and performance across relevant groups or operating conditions.
• Document assumptions, methods, experiment results, and limitations.
• Maintain reproducible code and workflows using version control and testing.
• Collaborate with domain experts, data engineers, researchers, and software teams.
• Support model integration, monitoring, and updates within the assigned remit.
• Present findings and recommendations to technical and nontechnical stakeholders.
• Follow privacy, security, and responsible AI practices.

Role-Specific Responsibilities

• Machine Learning Analyst: Explore datasets, develop baseline models, and interpret results to support defined decisions or use cases.
• Machine Learning Specialist: Independently develop and improve machine learning solutions, guide technical choices, and resolve complex modelling or performance issues.
• Machine Learning Research Associate: Review literature, implement research methods, conduct experiments, and contribute to research reports under appropriate supervision.

Qualifications

• Relevant experience in machine learning, data science, statistical analysis, or research; academic projects may be considered for junior roles.
• Strong grounding in statistics, probability, linear algebra, and machine learning fundamentals.
• Proficiency in Python and familiarity with relevant modelling libraries.
• Working knowledge of SQL and data preparation techniques.
• Understanding of model selection, validation, evaluation metrics, and overfitting.
• Strong analytical, problem-solving, and documentation skills.
• Ability to explain results accurately without overstating model capabilities.
• Effective communication and collaborative working skills.
• A degree in computer science, statistics, mathematics, engineering, economics, or a related field, or equivalent demonstrated technical experience.
• Machine Learning Specialist: Experience independently delivering models and assessing practical implementation constraints.
• Machine Learning Research Associate: Ability to critically read research papers and conduct structured experiments.

Preferred Qualifications

• Experience with deep learning, natural language processing, computer vision, or another relevant specialty.
• Familiarity with experiment tracking, cloud computing, or distributed processing.
• Knowledge of interpretability, uncertainty estimation, fairness evaluation, or robustness testing.
• Experience with deployment pipelines and production model monitoring.
• Publications, open-source contributions, or a portfolio of reproducible projects.
• Relevant postgraduate study or research experience.

Scope by Role

• Machine Learning Analyst: Provides data exploration, modelling, and analytical insights for defined problems.
• Machine Learning Specialist: Owns complex modelling work and provides specialist implementation guidance.
• Machine Learning Research Associate: Supports systematic investigation of machine learning methods and research questions.