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Operations Analyst

flexiple

  • Bengaluru, Mumbai, Delhi NCR, Hyderabad, Pune, Chennai, Kolkata, Ahmedabad, Remote (India)
  • β‚Ή5 LPA - β‚Ή8 LPA
  • Fresher (0-1 Yrs)
  • Posted Today
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About the role

Flexiple is a managed marketplace that connects global enterprises with top‑tier talent in India. Over the past few years, it has built a reputation for delivering high‑performing, remote‑first teams that drive measurable impact for its clients. The company’s culture emphasizes flexibility, merit‑based growth, and a strong focus on outcomes rather than hours logged. As a partner of a leading global logistics firm, Flexiple is now expanding its India operations‑analytics team to bring data‑driven insights to a high‑volume shipping network. The Operations Analyst role sits at the intersection of logistics, data science, and business operations. Reporting to the Operations Analytics Lead, you will be responsible for turning raw shipment, throughput, and service‑level data into actionable intelligence that helps keep the network running smoothly and on schedule. You will work closely with operations managers, account teams, and senior leadership, providing them with the numbers they need to make informed decisions. Key responsibilities include: 1. Track daily shipment volumes, SLA adherence, and exception rates across all hubs. 2. Analyse route efficiency, capacity utilization, and turnaround‑time data to identify bottlenecks. 3. Build and maintain recurring cost‑per‑shipment and service‑level performance reports. 4. Design interactive dashboards (Powerβ€―BI/Tableau) that are reviewed weekly by operations managers and leadership. 5. Document process gaps, suggest improvements, and support implementation without owning execution. 6. Respond to ad‑hoc data requests from operations, account, and finance teams. 7. Conduct root‑cause analysis for any SLA breaches and propose corrective actions. 8. Collaborate with the data engineering team to ensure data pipelines are reliable and up‑to‑date. 9. Mentor junior analysts on best practices in data handling and reporting. 10. Stay updated on logistics trends and incorporate relevant metrics into reporting frameworks. Tech stack: Advanced Excel/Google Sheets, SQL for data extraction, Powerβ€―BI or Tableau for visualization, basic Python/R for data manipulation (optional). Familiarity with logistics management systems is a plus. Growth path: Starting as an Operations Analyst, high performers can progress to Senior Analyst, Analytics Lead, and eventually to Product or Operations Management roles within the global logistics partner. The role offers exposure to end‑to‑end supply‑chain processes, making it an excellent springboard for a career in analytics or logistics strategy. Why join Flexiple? You will work on real‑world logistics challenges for a global leader, enjoy a remote‑first setup with flexible hours, and receive mentorship from seasoned professionals. The company’s performance‑driven culture ensures that your contributions are recognized and rewarded, and you will gain visibility across multiple business functions, accelerating your professional growth.

Eligibility & process

Who can apply

Bachelor's degree in Engineering, Commerce, Science or related field; Minimum 60% aggregate (or CGPA 6.5/10); Graduating batch 2020‑2024; No active backlogs; Strong analytical mindset and proficiency in Excel/Google Sheets; Good command of written and spoken English.

Skills & stack

Advanced Excel Google Sheets SQL Power BI Tableau Data Analysis Reporting Logistics Knowledge

Selection process

  1. Round 1: Internal HM Review
  2. Round 2: Flexiple Interview
  3. Round 3: Profile Review
  4. Round 4: Tech Interview 1
  5. Round 5: Tech Interview 2
  6. Round 6: Tech Interview 3
  7. Round 7: Founder Interview

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Advanced Excel, Google Sheets, SQL, Power BI, Tableau, Data Analysis, Reporting, Logistics Knowledge) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion flexiple Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join flexiple as a Operations Analyst?
Highlight flexiple's market reputation, recent tech innovations, and how your skills in Advanced Excel directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
flexiple β‚Ή5 LPA - β‚Ή8 LPA
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