Data Scientist
15 hours ago
Role Purpose
In addition to applying advanced statistical and machine learning techniques, the Data Scientist takes on additional responsibilities related to team leadership and technology focus. This role requires strong technical expertise and the ability to guide and mentor a team of data scientists.
Roles & Responsibilities
- Collaborate with stakeholders to define data science strategies, objectives, and priorities.
- Drive the development and deployment of complex predictive models and machine learning algorithms.
- Accountable for data science input into the design, development, and implementation of major solutions, and where necessary methodological direction provided to direct reports.
- Accountable (owns) the completeness and accuracy of the Analytics Requirements.
- Owns the configuration and Implementation of data science models using the agreed technologies components (e.g., Python).
- Able to manage multiple deployments concurrently.
- Ownership of Analytics Quality assurance and testing for solutions within the scope of the domain.
- Lead and manage data scientists assigned within product development, providing technical guidance, mentorship, and performance feedback.
- Communicate data science initiatives and results to senior management and other relevant stakeholders.
- Update the team with the latest advancements in data science technologies and tools and assess their potential impact on the team's work.
Requirements
- Advanced degree or equivalent experience in the quantitative field: Statistics, Mathematics, Computer Science, Engineering, Data Science, or Analytics.
- 4+ years of experience in statistical / ML data modeling and business intelligence/data mining.
- Diverse knowledge of where to apply and how to evaluate results of statistical, machine learning, and data mining techniques.
- Fluency in programming languages\frameworks: SQL, Python, TensorFlow.
- Strong visual design skills used in creating information-dense, easy-to-understand reports and dashboards (with examples): Tableau, MS Power BI, Python, or JavaScript-based visualizations.
- Working knowledge of Agile and DataOps.
- Must be able to work collaboratively with cross-functional cross-geographical teams to analyze and understand business needs.
- Good knowledge of at least two functional areas: customer relationships and sales, freight forwarding/express/e-com/logistics operations, pricing, customer service, aviation operations, finance, and billing.
- Excellent communication and presentation skills (English), including translating technical concepts for non-technical stakeholders.
Tell employers what skills you have
Tableau
Machine Learning
Big Data
Data Modeling
Data Mining
SQL
Python
Presentation Skills
Statistics
Data Science
Visualization
Product Development
Power BI
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