Operations Analytics Specialist, HQC

Job Summary

Position Overview. The Operations Analytics Specialist is responsible for leveraging data, analytics, and advanced technology to improve operational efficiency, productivity, and decision-making. The role will work closely with regional and Head Office teams to analyze complex operational data, identify improvement opportunities, develop scalable analytical solutions, and enable data-driven performance management across operations.

Job Purpose. To drive operational excellence through data analytics, business modelling, process optimization, and advanced analytics. The role will convert complex operational data into actionable insights, develop analytical and predictive solutions, establish effective KPI mechanisms, and support regions and business stakeholders in making informed decisions that improve efficiency, productivity, service quality, and cost effectiveness.

Responsibilities

• Data analysis and business insights: Analyze large and complex operational datasets to identify trends, gaps, opportunities, and root causes.
• Translate data into actionable insights and recommendations to support operational and business decisions.
• Conduct exploratory, diagnostic, and advanced analytics to identify opportunities for improvement.
• Develop business models, analytical models, and scalable data solutions to address operational requirements.
• Build solutions using Python, SQL, Spark/PySpark, and Azure Databricks.
• Support the development and implementation of data-driven solutions aligned with business objectives.
• Identify opportunities to improve operational processes through data analysis and analytics.
• Develop analytics-driven interventions to improve productivity, efficiency, and cost effectiveness.
• Support process digitization and automation initiatives to reduce manual effort and improve process accuracy.
• Develop analytical reports, dashboards, performance views, and decision-support tools for operational reviews.
• Provide timely insights to regional and HO stakeholders to support performance management and business decisions.
• Ensure analytical outputs are relevant, accurate, scalable, and aligned with stakeholder requirements.
• Establish and maintain mechanisms to monitor key operational KPIs and performance trends.
• Identify performance gaps and provide data-backed recommendations for corrective actions.
• Support continuous improvement through regular KPI tracking and analytics-led reviews.
• Identify and develop predictive analytics and advanced analytics use cases relevant to logistics and operations.
• Apply statistical modelling and machine learning techniques, where appropriate, to anticipate operational trends and improve decision-making.
• Deploy scalable analytics solutions with clearly defined business outcomes.
• Partner with regional and HO teams to understand operational challenges and translate them into analytics requirements.
• Resolve data and performance discrepancies in collaboration with relevant stakeholders.
• Provide analytics-based solutions to regional queries within agreed timelines and SLAs.
• Explore new-age analytics, automation, and machine learning applications to improve logistics operations.
• Identify opportunities to enhance analytics adoption and strengthen data-driven decision-making across the organization.

Qualifications

• Education: Bachelor's or Master's degree in Data Science, Analytics, Statistics.
• Experience: 3-5 years of experience in data analytics, preferably in supply chain, logistics, transportation, or operations domains. Prior exposure to supply chain optimization, predictive analytics, statistical modelling, or advanced analytics is desirable.

Skills

Technical Skills

• Python
• SQL
• Spark/PySpark
• Azure Databricks

Competencies

• Analytical Thinking - Strong problem-solving mindset with attention to detail.
• Communication - Ability to simplify complex data insights for diverse stakeholders.
• Collaboration - Strong interpersonal skills to partner with cross-functional and regional teams.
• Execution Excellence - Ability to deliver solutions under tight timelines.
• Innovation Mindset - Capability to explore new-age analytics and machine learning for logistics.

Key Performance Indicators

• Data Insight Delivery: >= 95% of identified operational decisions / business requirements supported with analytics.
• Process Optimization Impact: >= 10% efficiency improvement through analytics-driven interventions annually.
• Analytics Adoption/Decision Support: >= 90% of identified stakeholders regularly using analytical outputs for operational reviews and decision-making.
• Predictive Advanced Analytics Deployment: >= 3 predictive / advanced analytics solutions deployed annually with defined business use cases.
• Regional Collaboration: 100% of regional queries addressed within SLA.

Travel Required: 25%, 50%, 75%.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.