IT Manager - Analytics

Job Title: Senior Data Analyst

Location: Sharnam Metrolinks, Amraiwadi, Ahmedabad

Working Days: 6 Days a Week

Department: MDO

Reporting To: COO

Employment Type: Full-Time

Job Summary

We are seeking a highly analytical and detail-oriented Senior Data Analyst to lead data management, reporting, automation, and system development initiatives across the organization.

The role focuses on transforming raw data into meaningful insights, designing and implementing automated systems, strengthening data structures, and supporting cross-functional teams with accurate, actionable intelligence to drive strategic and operational business decisions.

Key Responsibilities

1. Data Management & Reporting

● Collect, clean, validate, and consolidate data from multiple internal and external sources.

● Prepare and deliver daily, weekly, and monthly MIS reports for management and departments.

● Design, develop, and maintain dashboards to track KPIs, performance metrics, and operational trends.

2. Database & Data Accuracy Management

● Manage and regularly update internal databases, spreadsheets, and reporting systems.

● Ensure data accuracy, consistency, integrity, and confidentiality across all platforms.

● Implement best practices for data validation, version control, and audit checks.

3. Data Analysis & Business Insights

● Analyze large and complex datasets to identify trends, patterns, gaps, and anomalies.

● Translate data findings into clear, actionable insights and recommendations to support

strategic and operational decision-making.

4. Reporting Automation, System Recommendation & Implementation

● Identify opportunities to replace manual or semi-manual processes with automated, data-driven systems.

● Design and implement automated reporting frameworks, dashboards, and data pipelines using Excel (Power Query, VBA, Macros), SQL, BI tools, and Python.

● Proactively suggest new automation tools, system enhancements, or integrations to

improve efficiency, accuracy, and scalability.

● Lead the end-to-end implementation of approved automation initiatives, including requirement gathering, system design, testing, deployment, and stabilization.

● Continuously monitor and optimize automated systems in line with business growth and evolving data needs.

5. Cross-Functional Coordination & Support

● Collaborate with Sales, HR, Finance, Operations, and other departments to understand

reporting and data requirements.

● Provide support for ad-hoc analysis, custom reports, and special data requests.

● Act as a data partner to department heads for decision support and performance tracking.

6. Documentation & Compliance

● Maintain complete and updated documentation for MIS processes, reports, data models,

automation logic, and system changes.

● Ensure compliance with company data governance policies and applicable data protection standards.

System Development & Data Structuring Responsibilities

● Study and understand departmental workflows to evaluate how data is generated, processed, and utilized.

● Review existing manual and digital data systems to identify operational gaps, risks, and

mprovement opportunities.

● Recommend structured data models, reporting formats, and storage solutions aligned with

business requirements.

● Coordinate with department heads to define data structures, access levels, and reporting

standards.

● Implement new or upgraded data systems (Excel-based models, cloud platforms, ERP

integrations) with minimal operational disruption.

● Design structured data formats and role-based access controls to ensure secure and

organized data management.

● Train employees on newly implemented systems and provide post-implementation

support.

● Monitor system performance, resolve issues, and continuously improve systems based on

user feedback and organizational growth.

Qualifications & Experience

● Bachelor’s degree in Commerce, Statistics, Computer Applications, or a related field.

● 3–5 years of experience in data analytics, reporting, or system automation roles.

● Strong analytical thinking, logical reasoning, and problem-solving abilities.

● High attention to detail with excellent organizational and documentation skills.

Technical Skills (Must Have)

● Advanced Excel: Power Query, Power Pivot, VBA basics, Macros, Charts

● BI Tools: Power BI or Tableau (DAX, data modeling, dashboard optimization)

● Google Apps Script: Automation in Google Sheets, custom functions, triggers, API integrations, workflow optimization

● Vlook

Preferred Skills

● Strong verbal and written communication skills

● Ability to handle sensitive and confidential information responsibly

● Quick learner with a tech-savvy, improvement-driven, and solution-oriented mindset

About the Role

Work at the intersection of business and technology, supporting operations, data analysis, automation, and digital tools to improve efficiency and growth. 

 Responsibilities 

• Support business operations using tech tools (Excel, CRM, dashboards)  
• Analyze data and generate insights for decision-making  
• Assist in automation workflows and process improvements  
• Coordinate between tech and business teams  
• Help in implementing digital solutions and tools  

 Skills Required 

• Basic knowledge of Excel / Google Sheets  
• Good analytical and problem-solving skills  
• Understanding of business processes  
• Interest in technology and automation  

 Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO based on performance 

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

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Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

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Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

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Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

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Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

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Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

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Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

Analytics Lead – AI & Decision Intelligence

Technical Leadership | People Management | Client Engagement | AI / Data / ML

About the Role

Our client is an enterprise AI and Decision Intelligence product company building advanced solutions for banking,

financial services and insurance. Its work spans predictive analytics, Machine Learning, Generative AI and Agentic AI,

with a strong focus on production-ready deployment, explainability, governance and measurable business outcomes.

The company is looking for an experienced Analytics Lead – AI & Decision Intelligence to lead a multidisciplinary team

of Data Scientists, ML Engineers, AI Engineers and other technical specialists.

This is a technical leadership, people management and client-facing role. The successful candidate is not expected to

be a hands-on expert in every area of AI, Data Science and Machine Learning. Instead, the ideal person will bring deep

expertise in at least one core AI/Data/ML discipline, together with the technical breadth and managerial capability to

lead specialists across multiple domains.

You will provide direction to technical teams, translate business problems into AI-led solutions, drive successful

delivery, and act as a key interface between highly technical teams and clients. A critical part of the role is the ability to

simplify complex technical concepts and communicate them clearly to senior and non-technical stakeholders.

What You’ll Do

 Lead and manage a multidisciplinary team of Data Scientists, ML Engineers, AI Engineers and Analytics

professionals.

 Provide technical direction across AI, Machine Learning and Data Science initiatives while enabling specialists to

own their areas of expertise.

 Translate business and customer requirements into appropriate analytical and AI solution approaches.

 Own delivery across scope, priorities, timelines, technical quality and business outcomes.

 Review and challenge technical approaches, solution designs and architecture without needing to be the hands-on

specialist in every area.

 Mentor, develop and motivate technical team members and build a strong culture of collaboration and

accountability.

 Establish and reinforce best practices around model development, deployment, governance, monitoring and

continuous improvement.

 Work closely with Product, Engineering, Sales and Customer Success teams on solution development and product

roadmaps.

 Lead client workshops, technical discussions and solution presentations.

 Explain complex AI and analytics concepts in simple, business-friendly language to senior and non-technical

stakeholders.

 Support pre-sales, solutioning and customer-facing technical engagements.

Technical Capabilities

Candidates should have strong exposure to the broader AI and Data Science ecosystem. Relevant capabilities include:

 Machine Learning & Deep Learning

 Statistical Modeling

 Python and SQL

 Data Science frameworks such as Scikit-learn, XGBoost, LightGBM, TensorFlow or PyTorch

 Data Engineering concepts and Feature Engineering

 Predictive and Prescriptive Analytics

 Model Explainability

 MLOps, CI/CD, model deployment and monitoring

 Generative AI and Large Language Models (LLMs)

 Retrieval-Augmented Generation (RAG)

 AI Agents and Agentic AI architectures

Analytics Lead – AI & Decision Intelligence | LinkedIn Job Description

 Prompt Engineering

 Responsible AI, model governance and regulatory considerations

 Cloud platforms such as AWS, Azure or Google Cloud

Important: You do not need to be an expert in all of the above. We are looking for deep expertise in at least one core

area of AI, Data Science, Machine Learning, ML Engineering, Generative AI, MLOps or Data Engineering, combined with

sufficient breadth to effectively lead experts in adjacent areas.

What We’re Looking For

 5–8 years of overall experience in AI, Data Science, Machine Learning, Analytics, Data Engineering or a related

technology discipline.

 Proven experience leading or managing teams of Data Scientists, ML Engineers, AI Engineers or similar technical

professionals.

 Strong people management, mentoring, delegation and team-building capabilities.

 Experience leading complex technical projects involving multiple specialist disciplines.

 Strong client-facing, stakeholder management and project delivery skills.

 Ability to communicate technical concepts clearly to non-technical audiences.

 Strong presentation skills and confidence engaging senior business stakeholders.

 Ability to balance technical considerations with business priorities and delivery objectives.

 Strong problem-solving, decision-making, organisational and managerial skills.

Preferred Experience

 Experience delivering AI or analytics solutions in Banking, Financial Services or Insurance.

 Exposure to use cases such as credit risk, fraud detection, customer acquisition, marketing analytics, collections,

deposits or pricing analytics.

 Experience working in an AI product, technology consulting or enterprise analytics environment.

 Exposure to Generative AI, LLM and Agentic AI programmes.

 Understanding of Responsible AI, explainability and regulatory considerations.

Education

 Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Statistics, Mathematics or a

related discipline.

 MBA preferred, but not essential.

The Profile We’re Looking For

We are looking for a technical leader who can lead experts — not someone expected to be the expert in everything.

Technical Depth + People Leadership + Client Management + Delivery Ownership

If you have strong expertise in one area of AI/Data/ML, have successfully managed technical teams, and can

confidently engage with both technologists and business leaders, we would like to hear from you.