The Analytics Lead is responsible for analyzing complex datasets of ships and other MOL data to derive actionable insights and help make data-driven decisions.
Actively proposes strategies to reduce GHG through data analysis findings by working with other data analysts.
- STATEMENT OF DUTIES & RESPONSIBILITIES
3.1. Build, develop, and maintain data models, reporting systems, data automation systems, dashboards, and performance metrics support that support key business decisions.
3.2. Leads the team using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
3.3. Performs intermediate to advanced data analysis techniques including statistical techniques to derive insights from data.
3.4. Works closely with junior analytics members to derive accurate results and implement strict quality on sharing findings through reports.
3.5. Continuously enhance domain knowledge of maritime operations and engineering concepts among junior team members, fostering high-value insights.
3.6. Exhibit advanced proficiency in technical tools such as MS Excel, Power BI, and R/Python for statistical analysis, and train analysts in their effective application.
3.7. Utilize various statistical methods, machine learning, and predictive modeling to derive insights from large datasets.
3.8. Supervises the junior analytics team members to capture and transform data effectively.
3.9. Provides mentorship fostering a culture of continuous learning and improvement.
3.10. Keeps up to date with industry trends, tools, and technologies in data analytics to enhance the team's capabilities.
3.11. Organize and drive successful completion of data insight initiatives through analysts and data scientists and collaboration with stakeholders.
3.12. Communicates results and business impacts of insights initiatives to stakeholders within and outside the company.
3.13. Performs other tasks that may be assigned by management from time to time.
Reports to: Manager
Directly Supervises: Data Specialist, Business Intelligence Developer, Data Scientist
Project Section: Analytics
JOB SPECIFICATION
4.1. Education
4.1.1. Bachelor / College degree in Engineering, Statistics, Mathematics, Computer Science, or equivalent.
4.2. Experience
4.2.1. 5 years of supervisory experience in related work
4.2.2. 3+ years of experience in data analytics, with a strong emphasis on technical analysis.
4.2.3. Experience with big data technologies is an advantage.
4.2.4. Proven track record of leading analytics projects from conception to implementation.
4.3. Skills
4.3.1. Advanced knowledge of MS Office Package: Excel, PowerPoint, Word, etc.
4.3.2. Proficiency in data manipulation languages (e.g., SQL, Python, R) and data visualization tools (e.g., Tableau, Power BI).
4.3.3. Strong understanding of statistical analysis, machine learning, and data modeling techniques.
4.3.4. Excellent problem-solving skills and the ability to communicate complex concepts to non-technical stakeholders.
4.3.5. Strong knowledge of SQL and experience with databases.
4.3.6. Familiarity with data warehousing concepts and ETL processes.
4.3.7. Experience in Data Results Interpretation and Content Creation (Facts, Impact, Recommendations)
4.3.8. Effective presentation skills for communicating ideas.
4.4. Other Skills
4.4.1. Strong analytical skills with an initiative for innovative thinking.
4.4.2. Excellent planning, leadership, and decision-making skills
4.4.3. Strong oral and written English communication skills.
4.4.4. A highly motivated, structured, and quality-driven individual possessing strong initiative and excellent people skills.
4.4.5. Demonstrates team collaboration and cohesion.
4.4.6. Background in the shipping/maritime industry is an advantage.
Transportation and communication allowance (fixed amount paid in the payroll)
2x a month company-paid for lunch
Eligibility for performance bonus for regular employees who have stayed with the company a minimum of 1 year. Average is at least 1 month's worth of salary
HMO with 2 qualified dependents
Work schedule: Monday to Friday 8:00 - 17:00
