Data Analyst

Round 1: Online Assessment (aptitude + technical coding) → Round 2: Technical Interview (case studies, analytics concepts, tools) → Round 3: HR Interview (fit, motivation, cultural alignment)

Accenture promotes a collaborative and inclusive work environment where learning is continuous and employees are encouraged to experiment with new technologies. The firm offers clear career progression, global mobility options, and a balanced approach to work‑life integration through flexible hours and remote‑work policies.

Accenture's interview process typically starts with an online assessment that tests quantitative aptitude, logical reasoning and basic coding. Successful candidates move to a technical interview where they solve case‑based analytics problems, discuss past projects, and demonstrate proficiency in tools like Python or SQL. The final HR round focuses on cultural fit, communication skills and career aspirations. Preparation should include mock tests, revisiting core statistical concepts, and practicing data‑driven case studies.

Graduation (B.Tech/B.E/M.Tech/M.Sc) in Computer Science, Statistics, Operations Research, Industrial Engineering or related fields; Minimum 60% aggregate (or CGPA 6.5/10); No active backlogs (max 2 allowed at the time of application); Experience of 2-5 years in analytics, data science or supply‑chain consulting; Strong academic record and demonstrated problem‑solving ability.

Accenture is a global professional services company with leading capabilities in digital, cloud and security. With more than 700,000 people serving clients in over 120 countries, Accenture helps organizations transform and stay ahead of disruption. The Strategy & Consulting arm, especially the Global Network – Data & AI practice, partners with Fortune‑500 firms to turn data into actionable insights, enabling smarter decisions across functions such as finance, marketing, and supply chain. The practice is known for its collaborative culture, continuous learning programs, and a strong focus on innovation through AI, machine learning and advanced analytics. The role of Ind & Func AI Decision Science Analyst sits at the intersection of data science and supply‑chain management. As part of the Supply Chain Analytics team, you will work on end‑to‑end analytical solutions that help clients forecast demand, optimise inventory, and improve logistics efficiency. You will translate complex business problems into data‑driven models, communicate insights to senior stakeholders, and contribute to the development of reusable analytical assets for the practice. Key Responsibilities: 1. Design and implement statistical and machine‑learning models for demand forecasting, inventory optimisation and network design. 2. Conduct time‑series analysis and develop predictive algorithms to anticipate supply‑chain disruptions. 3. Translate client business requirements into analytical solutions, preparing clear documentation and visualisations. 4. Collaborate with cross‑functional teams (operations, IT, finance) to integrate analytics into existing business processes. 5. Perform data extraction, cleaning and transformation using SQL, Python or R. 6. Validate model performance, conduct sensitivity analysis and recommend improvements. 7. Create dashboards and interactive reports using Power BI/Tableau to convey insights. 8. Participate in asset development initiatives, building reusable code libraries and best‑practice templates. 9. Stay updated with emerging AI/ML techniques and propose innovative applications for supply‑chain challenges. 10. Support client workshops and presentations, articulating technical concepts in business language. Tech Stack: Python, R, SQL, Power BI/Tableau, Azure ML, Spark, statistical packages (statsmodels, scikit‑learn), optimization libraries (PuLP, Gurobi). Growth Path: Analysts typically progress to Senior Analyst, Consultant, Manager and eventually to Principal/Managing Director, with opportunities to lead large‑scale transformation programs and specialize in industry verticals. Why Join Accenture? You will work on high‑impact projects for global brands, gain exposure to cutting‑edge AI tools, and benefit from a culture that values diversity, mentorship, and continuous upskilling. The firm’s strong emphasis on employee development, flexible work arrangements, and robust performance‑linked rewards make it an attractive destination for ambitious data professionals.