Desired candidate profile:

• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Analyze large amounts of information to discover trends and patterns
• Experience with Computer Vision, NLP or Recommendation Systems would be an added advantage
• Build predictive models and machine-learning algorithms
• Combine models through ensemble modeling
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams
• Proven experience as a Data Scientist or Data Analyst
• Experience in data mining
• Understanding of machine-learning and operations research
• Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
• Analytical mind and business acumen
• Strong math skills (e.g. statistics, algebra)
• Problem-solving aptitude
• Excellent communication and presentation skills
• Bachelors or Masters degree (preferably in computer science or statistics) OR practical experience on freelancing projects, open source contribution, rank in coding challenges or stack overflow.

Technology Stack: 

• Scripting Language: Python
• Data Science Libraries/Frameworks: Tensorflow/Pytorch (Should know at least one but should be comfortable to switch if needed), Pandas, Sklearn, Numpy, Matplotlib, Seaborn
• API Frameworks: Flask or FastAPI
• Serving Frameworks: TFServe, TorchServe, MlFLow,
• MLOps Frameworks: MlFlow (Optional but an asset)
• Cloud: AWS, Azure, GCP