Machine Learning Expert

Lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.

Evaluate current ideas/solution/processes by performing statistical analysis to resolve data set problems and enhancing the accuracy of predictive automation capabilities.

Key accountabilities and decision ownership:

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Managing available resources such as hardware, data, and personnel so that deadlines are met
• Analysing the ML algorithms that could be usedto solve a given problem and ranking them by their success probability
• Exploring and visualizing data to gain an understanding of it, then identifying differencesin data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, and/or ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed
• Finding available datasets online that could be used for training
• Defining validation strategies
• Defining the pre-processing or feature engineering to be done on a given dataset
• Defining data augmentation pipelines
• Training models and tuning their hyperparameters
• Analysing the errors of the model and designing strategies to overcome them
• Deploying models to production

Core competencies, knowledge and experience:

• Proficiency with a deep learning framework such as TensorFlow or Keras
• Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
• Expertise in visualizing and manipulating big datasets
• Experience with Linux/Unix Systems
• Ability to select hardware to run an ML model with the required latency
• Strong analytical skills
• High attention to detail
• Innovation and creativity
• Ability to work with large, complex datasets

Must have technical / professional qualifications:

• Data science certification
• Python certified proficiency
• Experience working closely in a team/squad/tribe using agile methodologies Scrum and/or Kanban, practicing DevOps and Continuous Delivery / Integration