Job description
PRIMARY JOB DESCRIPTION
Provide industry insight as well as technical and analytical support using machine learning, deep learning, pattern matching, data visualisation, and predictive modeling tools to produce analysis and algorithms that help businesses make better decisions.
Build advanced analytics applications from structured and unstructured data on various technology platforms including cloud and big data platforms.
Execute analytics with the right balance of business and technical skills
Require a combination of a sharp analytical mind with hands-on experience in Data Science, ideally in advanced quantitative research, plus a natural gift for communicating and presenting complex analytical findings to stakeholders.
Key areas of responsibilities (scope)
Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices.
Identifies valuable internal and external data sources, automates collection processes and enriches data assets through data science methodologies
Analyzes large amounts of information to discover trends and patterns
Presentes information using data visualization techniques
Proposes and builds innovative and effective data science solutions and strategies to address topmost business challenges
Executes projects in agile methodology
Leads discovery processes with business stakeholders to identify the business requirements and the expected outcome
POSITION QUALIFICATIONS AND REQUIREMENTS
- Degree in Data Science, Computer Science, Engineering, Mathematics, Statistics or a related field with solid experience in Machine Learning and Deep Learning and exposure to big data and cloud based analytics.
- Strong understanding of a business domain (eg. Supply Chain, Marketing, Revenue Management). Desired industry expertise in the maritime sector
- Coding skills in Python, and ideally in other languages like R, SQL, Hive Sql, C++
- Hands-on experience with Python libraries such as Pandas, NumPy, sklearn, tensorflow
- Demonstrated ability to solve business problems involving one more more data science problem classes (classification, forecasting, natural language understanding, computer vision, quantitative optimization)
- Ability to communicate data science solutions that business stakeholders can understand
