AI/ML Analyst

Job Description

The AI/ML analyst is a person whose primary focus should be on researching, building, and designing self-running artificial intelligence (AI) systems to automate predictive models. He/she is responsible for designing and creating AI algorithms capable of learning and making predictions that define Machine Learning. He/she would be working closely with Data Architect, administrators, and data analysts.

What you will do:

  • Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models
  • Transforming data science prototypes and applying appropriate ML algorithms and tools
  • Ensuring that algorithms generate accurate user recommendations.
  • Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Developing ML algorithms to analyze huge volumes of historical data to make predictions.
  • Running tests, performing statistical analysis, and interpreting test results.
  • Documenting machine learning processes.
  • Keeping abreast of developments in machine learning
  • Researching and implementing ML algorithms and tools
  • Selecting appropriate data sets
  • Picking appropriate data representation methods
  • Identifying differences in data distribution that affects model performance
  • Verifying data quality.
  • Transforming and converting data science prototypes.
  • Performing statistical analysis.
  • Running machine learning tests.
  • Using results to improve models.
  • Training and retraining systems when needed.
  • Extending machine learning libraries.

What you will need to succeed:

  • Bachelor s/Master s Degree in Computer Science, Mathematics and/or Statistics or an equivalent combination of education and experience.
  • 3-5 Years of experience in AI/ML Analyst role.
  • Proficiency with a deep learning framework such as TensorFlow or Keras
  • A dvanced proficiency with Python, Java, and R code writing.
  • Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture
  • Advanced math and statistics skills, surrounding subjects such as linear algebra, calculus, and Bayesian statistics.
  • Certification in machine learning, neural networks, deep learning, or related fields will be an added advantage.
  • Good oral written communication skills.
  • Strong analytical, problem-solving and teamwork skills.
  • Software engineering skills.
  • Experience in Data Science.
  • Coding and programming languages, including Python, Java, C , C, R and JavaScript.
  • Experience in working with ML frameworks.
  • Understand data structures, data modeling and software architecture.
  • Knowledge in computer architecture.

Key Skills

Data modeling; Coding; Analytical; Artificial Intelligence; Machine learning; Javascript; Data structures; Data quality; Python

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