Allcargo Logistics - Manager - Data Analytics

Manager - Data Analytics

Description:

The Data Analytics Team Leader/Manager will spearhead the analytics function, translating complex data into actionable insights that drive efficiency, enhance customer satisfaction, and optimize operational performance.

This leadership role requires a blend of technical ex-pertise, project management capabilities, and the ability to mentor and guide a team of data analysts to meet strategic business objectives. This is a highly visible, mid-to-senior level role where you will manage the data analytics team, bridge the gap between technical analysts and business stakeholders, and ensure data integrity and accessibility across the organiza-tion.

You will translate the inputs provided (customer satisfaction, ad-hoc requests, score-cards, projects, automation) into strategic initiatives that optimize service delivery and oper-ational efficiency.

Key Accountability Area

Team Leadership & Development:

- Lead, mentor, and manage a high-performing team of data analysts, fostering a culture of data curiosity, accuracy, and professional excellence.

- Champion continuous learning initiatives, ensuring team members complete relevant certification courses and training programs to enhance skills and contribute to professional development goals.

Strategic Project Management:

- Drive all phases of analytic projects: understand business requirements, build data models, analyze results, and oversee successful implementation.

- Collaborate with cross-functional departments (Operations, Sales, Finance) to identify analytical opportunities and deliver impactful solutions that optimize logistical processes.

Operational Reporting & Automation:

- Manage the development, preparation, and timely distribution of monthly operational scorecards to key stakeholders, providing clear visibility into performance metrics.

- Design and implement a robust framework for report automation, migrating recurring reports from manual processes to efficient, automated solutions using modern BI tools.

Ad Hoc Analysis & Stakeholder Support:

- Oversee the intake and prioritization of ad hoc data requests from the business and stakeholders, ensuring timely, accurate, and relevant completion of unplanned or urgent analytical need

Customer Satisfaction & Performance Measurement:

- Implement and manage a Customer Satisfaction (CSAT) measurement program, surveying key internal customers to gauge the effectiveness and impact of the data analytics team's work.

- Utilize feedback from satisfaction scores to continuously improve service delivery and analytical support quality.

Qualification: Masters degree in quantitative fields such as Engineering, Computer Science, Statistics, Mathematics or Operations Management.

Work Experience:

- Minimum of 8-12 years of overall experience in data analytics, business intelligence, or a related field.

- Minimum of 3+ years of experience in a leadership/management role, managing a team of data analysts or data scientists.

Domain Expertise (Mandatory): Proven experience within the Logistics, Supply Chain, Express Distribution, or E-commerce sectors in India is essential.

Technical / Functional Competencies

- Proficiency in SQL and working with large, complex datasets.

- Strong command of data visualization tools (e.g., Microsoft Power BI, Tableau) for creating intuitive dashboard

- Experience with statistical programming languages (Python or R) for advanced analytics and modelling is highly preferred.

1. Data Analysis & Visualization

- Excel (Advanced): Pivot tables, Power Query, macros for quick analysis.

- BI Tools: Power BI, Tableau, Qlik for dashboards and reporting.

- Data Visualization Principles: Ability to present insights clearly for operational decisions.

2. Programming & Scripting

- Python: For data cleaning, statistical analysis, predictive modelling.

- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn.

- R: For statistical modelling and forecasting (optional but useful).

- SQL: Strong skills in querying large datasets from ERP/WMS/TMS systems.

3. Predictive & Prescriptive Analytics

- Machine Learning: Demand forecasting, route optimization, inventory prediction.

- Optimization Techniques: Linear programming, simulation models for supply chain efficiency.

The following skills and experience are considered a plus:

1. Data Engineering & Big Data

- ETL Tools

- Big Data Platforms

- Cloud Services

2. Domain-Specific Tools

- ERP/WMS/TMS Analytics

- GIS Tools

3. Data Governance & Quality

- Data Cleaning & Validation

- Knowledge of APIs

Behavioral Competencies

- Exceptional ability to translate complex data findings into clear, concise, and action-able business recommendations for executive leadership.

- Strong project management skills with the ability to manage multiple priorities in a dynamic, deadline-driven environment.

- Deep understanding of operational processes within the logistics/express delivery ecosystem.

- Excellent communication and interpersonal skills, capable of bridging the gap be-tween technical teams and non-technical business stakeholders.

- Problem Solving & Critical Thinking - Analytical mindset to resolve logistics challenges & Data-driven decision-making and scenario planning.

- Adaptability & Innovation - Embracing change, especially in tech-driven environments & Driving innovation through automation and digitalization.

- Customer Focus - Ensuring high service levels and customer satisfaction.

- Integrity & Accountability - Ethical leadership and responsible decision-making & Ownership of KPIs like on-time delivery, cost savings, and inventory accuracy.