About the opportunity:
As a Chief Data Scientist, you will provide technical leadership and direction to help address our client's strategic business and technology imperatives. The person will further scale innovation across the organisation through empowerment and management of company’s engineering, data science and infrastructure teams. As a member of the executive team, they will own and drive evolution of key strategic technologies and system architecture, with a focus on working effectively in a highly collaborative, cross-functional environment. We are seeking a high calibre individual who covers the breadth and depth of responsibilities outlined below.
Your Responsibilities
- Work closely with the application engineering, product management, and operational teams to lead the data science effort in designing, experimenting-with, and implementing machine learning and analytical systems
- Work to design and lead the data science effort on ground breaking new applications of machine learning and analytics technology within inventory management: producing quantitative, justifiable results to guide feature planning
- Build upon our Demand Forecasting and Inventory Optimization processes and practices
- Continually evolve the firm's data science toolkits and processes to leverage new technologies and best practice implementations
- Translate real-world inventory problems to data-driven, mathematical frameworks
- Lead and grow the Data Science team, including managing and coaching existing team members while recruiting talented individuals to join the team
- Lead the process of data exploration, hypothesis creation (from business and product goals), testing algorithms, scaling to large data-sets and validating results
- Developing end-to-end ML pipelines to automate internal and external processes
Basic Qualifications
- Master’s Degree in Computer Science, Statistics, Mathematics or a related field
- Strong domain knowledge within the Demand Planning and Time Series Analysis spheres
- 3+ years in product engineering, developing algorithms and applications in either B2B or B2C market segments
- 3+ years in a Sr. Data Scientist or Director capacity with responsibility of data engineering, ML engineering, or applied data science
- 3+ years managing software engineering and data science professionals in small- to medium-size organisations
Preferred Qualifications
- PhD in Data Science or a related field
- Experience with microservices architecture components, including Docker and Kubernetes
- Experience developing microservices to fit data cleansing, transformation and enrichment needs
- Experience with AWS cloud services: EC2, S3, EMR, RDS, Redshift, Athena and/or Glue
- Experience with Jira, Confluence and extensive experience with Agile methodologies
- Knowledge about data security and best practices
- Experience in developing flexible data ingest and enrichment pipelines to easily accommodate new and existing data sources
- Experience with software configuration management tools such as Git/Gitlab, Salt, Confluence, etc.
- Experience with continuous integration and deployment (CI/CD) pipelines and their enabling tools such as Jenkins, Nexus, etc
- Detailed oriented/self-motivated with the ability to learn and deploy new technology quickly