Lead Data Analyst-Internal Audit

Bridgestone Americas; Bengaluru Urban; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Bridgestone Americas in Bengaluru, India seeks a Lead Data Analyst to integrate data analytics into the internal audit lifecycle, delivering risk-focused insights and automations. You will work with a broad set of data sources, build descriptive and predictive models, and develop dashboards to support the audit plan.

You will lead analytics engagements, guide digital solutions, and mentor the DA team while collaborating with business partners to drive audit efficiency and insight generation.

Qualifications

• Undergraduate degree in a relevant field.
• 8+ years in digital/data tech, internal audit, investigations, internal controls, IT, data analytics, or risk management.
• Hands-on with data visualization and analytics tools.
• Experience applying AI/ML in business or audit contexts.
• Experience with Amazon Redshift, SAP ECC, and S/4HANA.
• Strong communication, stakeholder management, and project leadership.

Responsibilities

• Lead analytics-as-a-service engagements for audit planning and analytics.
• Derive insights from data to support decision-making.
• Design and implement digital analytics solutions to improve audit efficiency.
• Lead development of analytics and automation using Alteryx, Tableau/Power BI, SQL, Python.
• Provide project leadership, set goals, and mentor team members.
• Stay current with analytics tools and drive digital transformation in Internal Audit.
• Drive AI adoption across Internal Audit by identifying use cases and guiding implementations.
• Build relationships with leadership and stakeholders to communicate progress and results.

Skills

Tableau

Power BI

SQL

Alteryx

Python

R

Tableau Server

S/4 HANA

Amazon Redshift

Education

Undergraduate degree in Accounting, Analytics, Business, Finance, Information Technology, MIS

Tools

Tableau Server

Power BI

SQL

Alteryx

Python

R

Amazon Redshift

SAP ECC

S/4 HANA

Job description

Position: Lead Data Analyst – Internal Audit

Position Summary

The Lead Data Analyst is responsible for integrating data analytics into the internal audit lifecycle to provide risk-focused insights supporting the audit plan and enterprise risk management. This role involves performing and delivering risk-focused analytics, which include analyzing large data sets, creating descriptive and predictive models, developing dashboards, and implementing audit automation solutions. The position reports into the Internal Audit Analytics Project Manager and requires collaborating with the Internal Audit team and business partners to provide thought leadership and guide the design and development of complex analytical models and digital solutions.

Responsibilites

• Lead and deliver analytics-as-a-service engagement for areas of audit (i.e., planning, analytics, etc.) by understanding enterprise data, business processes, and business needs
• Demonstrate thought leadership to solve and provide digital solutions to address key business challenges and derive meaningful insights from data to decision-making.
• Support the Internal Audit Analytics Project Manager to design and implement digital solutions with high impact by focusing on improving the efficiency and effectiveness of the audit process, identifying novel risk-focused insights, and optimizing the end-user experience of dashboards and other analytical solutions.
• Lead the design and development of analytic and automation solutions to query, mine, and analyze large complex data sets leveraging data analytical tools (e.g., Alteryx, Tableau, Power BI, SQL, Python, etc.).
• Hands-on project leadership, including defining project goals and milestones, prioritizing and delegating tasks within the DA team to ensure timely and effective delivery, and training and guiding lower-level team members.
• Keep abreast of the latest advancements in analytics tools and technologies. Serve as a key advisor to audit leadership by identifying opportunities to enhance data acumen and drive digital transformation for internal Audit department.
• Drive the adoption and use of AI across Internal Audit teams by identifying use cases, guiding implementation of AI-enabled solutions, and promoting best practices that enhance audit quality, efficiency, and insight generation.
• Foster relationships with audit leadership and stakeholders to develop thorough understanding of business requirements and communicate work progress and results to both technical and non-technical audiences.

Qualifications

• Undergraduate degree in a relevant area (e.g., Accounting, Analytics, Business, Finance, Information Technology, MIS)
• 8+ years of working experience in digital/data technologies, internal audit, investigations, internal controls, information technology, data analytics, or risk management fields
• Technical expertise and previous hands-on experience with any of the following software tools: Data visualization tools (e.g., Tableau, Tableau server, Power BI, etc.); Data query/analytics tools (e.g., SQL, Alteryx, Alteryx server etc.); Programming and predictive tools (e.g., Python, R, etc.)
• Experience evaluating, implementing, or applying AI and machine learning solutions in business or audit-related contexts, with the ability to identify practical use cases and drive adoption.
• Experience with Amazon Redshift, SAP ECC and S/4 HANA
• Ability to work with large complex data sets from multiple data sources in de-centralized data environments
• Sound independent judgement, prioritization, and decision-making skills. Excellent critical thinking and problem-solving skills. Strong self-initiative, comfortable working with ambiguity and limited managerial involvement
• Ability to lead changes, work through challenges and setbacks.
• Strong stakeholder management with analytics teams, IT organizations, and business leadership.
• Strong organizational and project management skills. Ability to manage multiple projects at one time
• Strong communication and presentation skills
• Business fluency in Spanish and/or Portuguese preferred but not required