Work In Tech

Job Descriptions:

As a Data & AI technical lead, you will work on building and evaluating machine learning models to predict core business results. You’ll derive impactful insights from data to drive intelligence for the organization and its clients. You will work with your fellow data science team members to define and scope data science solutions to solve complex problems. You will help build, improve, and test robust statistical and machine learning solutions that will drive impact throughout the organization.

Qualifications:

• 2+ years of experience in data modelling, data migration, performance optimization, T-SQL, stored procedures, ETL Jobs
• 2+ years of experience developing Machine Learning models and working with AI frameworks.
• Familiarity with data structures, algorithms, statistics, and machine learning fundamentals.
• Hands-on development experience with at least 2 related databases such as SQL Server, Oracle, PostgreSQL, MySQL
• 2+ years of advanced programming skills in Python, with strong experience in data manipulation (Pandas, NumPy, SciPy, PySpark)
• Experience in designing and implementing data solutions that well takes care of database performance, data security and high availability
• Experience with at least 1 Extract, Transform, and Load (ETL) tool and 1 Business Intelligence (BI) tool.
• Skilful in performance tuning for both operational database and data warehouse
• Good knowledge of Enterprise Data warehouse (EDW)/Data lake and Business Intelligence (BI) solution
• Good English communication both speaking and writing skills, can confidently discuss with customer about technical approaches or issues in details
• Nice to have:
  • Good knowledge of Cloud based technologies e.g. Azure, AWS & GCP
  • Knowledge of NoSQL technologies: MongoDB, Cassandra, Graph Database is a plus
  • Knowledge of Git, Unix/Linux command-line, and CI/CD pipelines.
  • Familiarity with Docker, Kubernetes, and orchestrating machine learning models in production.
  • Experience working with RESTful APIs and social media data sources (Facebook, Twitter, LinkedIn, YouTube).