
Eligibility Criteria
Bachelor's or Master's degree in Statistics, Applied Mathematics, Computer Science, Economics or a related quantitative field. Minimum 60% aggregate (or CGPA 6.0/10) in the qualifying degree. No active backlogs at the time of joining. Fresh graduates as well as candidates with 1β2 years of relevant data analysis experience are eligible. Preference given to candidates from the 2023β2025 batch.

Job Description & Key Responsibilities
ShrinQ Consulting Group is a fastβgrowing analyticsβfocused consulting firm that helps enterprises across manufacturing, retail, and financial services turn raw data into actionable business strategies. Founded a few years ago, the company has built a reputation for delivering highβimpact insights through a blend of statistical rigor and modern visualization techniques. With offices in major Indian metros and a client base that spans startups to Fortune 500 companies, ShrinQ prides itself on a collaborative environment where curiosity is rewarded and continuous learning is part of the daily routine.
The firmβs culture revolves around dataβdriven decision making, encouraging every employee to ask the right questions and challenge assumptions. Employees enjoy a flat hierarchy, regular knowledgeβsharing sessions, and mentorship programs that accelerate professional growth. Workβlife balance is respected, with flexible timings and occasional remote days, allowing analysts to maintain productivity without compromising personal commitments.
**Role Summary**
As a Data Analyst at ShrinQ, you will be the analytical backbone for multiple business units. Your primary mission is to translate complex data sets into clear, concise visual stories that empower stakeholders to make informed decisions. You will work closely with product managers, operations heads, and senior leadership to identify pain points, design analytical frameworks, and deliver insights that drive revenue, efficiency, and customer satisfaction.
**Key Responsibilities**
1. Understand dayβtoβday business challenges and translate them into analytical problems.
2. Gather, clean, and integrate data from heterogeneous sources such as relational databases, CSV files, and APIs.
3. Perform exploratory data analysis to uncover trends, outliers, and hidden patterns.
4. Develop and maintain SQL queries and stored procedures for recurring reporting needs.
5. Build interactive dashboards and visualizations using tools like Tableau or Powerβ―BI to present findings in an intuitive manner.
6. Conduct adβhoc deepβdive analyses to answer specific business questions and support strategic initiatives.
7. Document analytical methodology, assumptions, and results to ensure reproducibility and knowledge transfer.
8. Collaborate with crossβfunctional teams to implement dataβdriven recommendations and monitor their impact.
9. Stay updated with emerging analytics techniques, statistical methods, and visualization best practices.
10. Participate in regular review meetings, presenting insights and actionable recommendations to senior leadership.
**Tech Stack**: SQL, Python (pandas, numpy), Excel, Tableau/Powerβ―BI, basic statistical packages (R or Pythonβs statsmodels).
**Growth Path**: Junior Analyst β Analyst β Senior Analyst β Lead Analyst β Analytics Manager β Director of Analytics. The firm encourages certifications (e.g., Tableau Desktop Specialist, Google Data Analytics) and offers internal training to fastβtrack career progression.
**Why Join ShrinQ**: You will work on realβworld problems for highβprofile clients, gain exposure to endβtoβend analytics workflows, and be mentored by industry veterans. The supportive culture, clear promotion ladder, and emphasis on workβlife harmony make ShrinQ an ideal launchpad for ambitious data professionals.