Requirements:
Education: Bachelor’s degree (IT/Software Enginnering/Mathematics)
Work experience: 3+ years
Strong expertise in:
Machine Learning and Data Science
Statistics (probability distribution, hypothesis testing)
Classical ML algorithms (Linear Regression, Decision Trees, SVM, Clustering, etc.)
MLOps (BentoML, Docker, Kubernetes, KubeFlow, KNative)
Python (PyTorch or Tensor)
General programming skills (OOP, OO design, MVC, Design patterns)
Solid understanding of ML/DS processes (from data preparation to model deployment)
Proven portfolio of successful projects
Participation in team projects
Good verbal and written communication English skills (Upper Intermediate level)
Experience in data extraction, cleansing, and preparation for ML training and test data sets
Experience in analysis of structured and unstructured / semi-structured data (e.g. raw text, json, xml)
Statistical Analysis & Modelling experience
Good knowledge of Predictive Modelling, Regression and Classification techniques
Good knowledge of Deep learning tools and techniques
Understanding and knowledge of Natural Language Processing (NLP) applications
Any BigData platform knowledge and/or experience (Apache Spark, Hadoop, Hive etc)
Will be a plus:
Hackathons/Kaggle experience
Data Visualisation (e.g. using Python, Tableau, R Shiny)
Hands on experience developing with relevant Python toolkits
Responsibilities:
Bring new ideas in software development
Leverage industry knowledge and stay close to technology developments
Collaborate with cross-functional teams