Analyst, Data Analytics

Job summary

Seeking a Data Analytics Analyst to work with cross-functional teams to develop data infrastructure, create analytical models, and generate insights business and operations insights that will improve performance across all facets of the business. Your work will directly impact the efficiency and effectiveness of our transportation operations, commercial and go to market activities and back office functions.

This position is integral to a wide range of strategic priorities within the organization with exposure to many internal and external stakeholders, including executive leadership, and the ability to grow the role beyond its existing scope over time.

Responsibilities

• Business & Operational Insights:
  Use knowledge of Trimac's complex data systems and business analytics to proactively source required data, identify trends and opportunities within the data based on an understanding of Trimac's business requirements/analytics. Create solutions and/or identify areas of improvement across all areas of our business including operations, commercial, and back office functions based on insights gleaned from analysis of our data and your understanding of our business and sector.
• Analytical Tools & Reporting:
  Independently build simple yet sophisticated tools, including traditional and predictive analytics, automated reporting and analysis, and visibility dashboards leveraging Excel, BI, and existing Trimac systems. Partner with business stakeholders in turning insights and recommendations into actions that improve performance through data backed decision making
  .
• Data Infrastructure, Architecture & Governance:
  Actively lead, maintain, and optimize the pipeline of data analytical projects, delineating between maintenance of the corporate level BI, and stakeholder specific analytics, reporting and visibility.
  Ensure data integrity and compliance with company data management, governance, and security is in line with the scope and breadth of projects/initiatives, updating those standards from time to time as required.
• Collaboration:
  Work closely with internal teams (e.g., operations, Sales, IT) to continually understand business needs, define data requirements, and deliver data solutions that improve performance.

Requirements and Qualifications:

• Experience:
  Minimum 2 years of experience in a data/business analyst role, with a focus on building and optimizing data infrastructure, analytical tools, and dashboards.
• Technical Skills:
• Strong proficiency in SQL and data query languages.
• Expertise in data visualization tools such as Tableau, Power BI, or similar platforms.
• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, Google Cloud).
• Familiarity with data integration, ETL processes, and API management.
• Advanced knowledge of Python, R, or other programming languages for data analysis and automation.
• Expertise in excel with experience in statistical analysis and forecasting methods.
• Analytical Mindset:
  Strong problem-solving skills with the ability to interpret complex data sets and generate actionable business insights independently.
• Business Acumen:
  Understanding of financial metrics/analytics and decision making process. Experience with standard financial analysis techniques such as Internal Rate of Return (IRR), Net Present Value (NPV), and other ROI calculations, to evaluate investment opportunities/calculate returns on investment
• Transportation/Logistics Knowledge:
  Experience in the transportation or logistics industry.
• Communication Skills:
  Ability to communicate complex technical data and analytical insights in a clear, concise manner to both technical and non-technical stakeholders.
• Education:
  Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related field.

Preferred Skills:

• Experience with transportation management systems (TMS) or fleet management software.
• Knowledge of machine learning models or predictive analytics in the context of logistics optimization.
• Strong project management skills and the ability to lead data-centric initiatives.