
Eligibility Criteria
Bachelor's or Master's degree in Statistics, Applied Mathematics, Computer Science, Engineering or related fields; minimum 60% aggregate (or CGPA 6.0/10); fresh graduates of 2023‑2025 batches; no active backlogs at the time of joining.

Job Description & Key Responsibilities
ShrinQ Consulting Group is a fast‑growing analytics and technology consulting firm that helps businesses turn raw data into actionable insights. Established in the early 2010s, the company has built a strong reputation for delivering data‑driven solutions across sectors such as finance, retail, healthcare, and logistics. With a workforce of over 500 professionals, ShrinQ emphasizes a collaborative culture where continuous learning and innovation are encouraged. The firm’s client‑centric approach has earned it multiple industry awards for excellence in data engineering and business intelligence.
As a Data Analyst at ShrinQ, you will be at the heart of the decision‑making engine. The role is designed for fresh graduates who are passionate about big data, love solving business problems, and enjoy translating complex datasets into clear, visual stories. You will work closely with senior analysts, data engineers, and business stakeholders to understand day‑to‑day challenges, extract relevant data, and present insights that drive strategic actions. This position offers a solid foundation for a career in analytics, with exposure to real‑world projects and mentorship from seasoned professionals.
Key Responsibilities:
1. Interact with business users to capture and clarify analytical requirements.
2. Extract, clean, and transform data from multiple sources using SQL and ETL tools.
3. Perform exploratory data analysis to identify trends, patterns, and anomalies.
4. Develop dashboards and visualizations using tools such as Power BI or Tableau to communicate findings.
5. Prepare ad‑hoc reports for senior management on short‑notice requests.
6. Automate repetitive reporting tasks to improve efficiency.
7. Collaborate with data engineering teams to ensure data quality and integrity.
8. Document analytical processes, assumptions, and results for future reference.
9. Stay updated with emerging analytics techniques and suggest improvements.
10. Participate in knowledge‑sharing sessions and contribute to the team’s best‑practice repository.
Tech Stack: SQL, Python (pandas, numpy), Excel, Power BI/Tableau, basic statistical packages (R or Python’s statsmodels). The role offers a clear growth path – from Analyst to Senior Analyst, then to Analytics Lead or Data Science roles, depending on performance and skill development. Joining ShrinQ means working in a supportive environment that values curiosity, offers regular training, and provides opportunities to work on high‑impact projects across diverse industries. The company’s emphasis on work‑life balance, flexible timings, and a merit‑based reward system makes it an attractive launchpad for aspiring data professionals.