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Customer Success - Operations (India Region)

Mercor

  • Remote
  • $90 - $120 per hour
  • 3 Years
  • Posted Today
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About the role

Mercor is a fast‑growing AI‑focused services company that partners with leading artificial‑intelligence labs and enterprises to train, evaluate, and improve frontier models. Founded by a team of ex‑researchers and product builders, Mercor builds a global talent network of domain experts who bring real‑world business judgment to AI systems that otherwise lack practical insight. The company operates fully remotely, offering flexible contracts to specialists across the world while maintaining a collaborative culture driven by data, rigor, and continuous learning.

The role of Business Operations Expert – Customer Success (India Region) sits at the intersection of business operations and AI model training. As a member of Mercor’s talent pool, you will not be hired for a single permanent position; instead, you will be matched to short‑term, high‑impact projects that require deep operational expertise. Each project typically lasts a few weeks and pays $90‑$120 per hour, depending on scope and complexity.

Your primary responsibility is to author, evaluate, and critique operational scenarios that AI models generate, ensuring that recommendations are realistic, implementable, and aligned with real‑world constraints.

Key Responsibilities

  • Write detailed operating problems, including process steps, constraints, quantitative data, and a reference solution for model evaluation.
  • Grade model‑generated operational analyses for feasibility, accuracy of forecasts, and relevance of metrics.
  • Identify and flag recommendations that would stall in practice due to headcount, system limitations, vendor terms, or approval hierarchies.
  • Provide clear, concise written feedback that explains your reasoning and highlights gaps in model outputs.
  • Collaborate with AI research teams to refine evaluation rubrics and improve model performance over time.
  • Stay updated on industry best practices in sales, customer success, supply chain, HR, and other business functions covered by the talent pool.
  • Participate in a short AI interview (β‰ˆ20 minutes) to verify expertise and fit for the pool.
  • Maintain confidentiality and avoid handling proprietary client data.
  • Track project hours and submit deliverables through Mercor’s portal for weekly payment processing.
  • Contribute to community knowledge by sharing anonymized case studies and insights with fellow experts.

Tech Stack & Tools: Advanced Excel/Google Sheets, SQL for data extraction, PowerBI/Tableau for visual analytics, basic scripting (Python or R) for data manipulation, project management tools (Asana, Trello), and collaborative platforms (Slack, Notion). Familiarity with AI model evaluation frameworks is a plus.

Growth Path: Starting as a contract expert, high‑performing contributors can earn higher hourly rates, gain access to larger, strategic projects, and eventually become senior domain leads who help design evaluation frameworks for entire business functions. Mercurial’s remote‑first model also allows you to build a diversified portfolio across multiple industries.

Why Join Mercor?: You will work directly with cutting‑edge AI research teams, influence the next generation of intelligent systems, and earn competitive hourly compensation while enjoying the freedom of remote, contract‑based work. The platform offers continuous learning, exposure to varied business challenges, and a community of like‑minded professionals across the globe.

Eligibility & process

Who can apply

Any graduate (B.Tech, B.E., B.Com, BBA, MBA, or equivalent) with a minimum of 60% aggregate (or CGPA 6.5/10). Must have completed the final year of study (batch 2024‑2027) or be a recent graduate. Candidates should have 1‑3 years of professional experience in any business operations function such as sales, customer success, supply chain, HR, or process improvement. No active backlogs are allowed at the time of application. Must be legally eligible to work in India and have a valid PAN and bank account for payments. H1‑B or STEM‑OPT candidates are not supported.

Skills & stack

Business Analysis Process Improvement Data Interpretation Stakeholder Management Advanced Excel SQL Power BI Project Management

Selection process

  1. Round 1: Short AI interview (β‰ˆ20β€―minutes) to assess domain knowledge and communication
  2. Round 2: Background verification and contract onboarding
  3. Project‑specific invitation with rate and scope details

Prep kit

19 resources
Study material 3
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 (Business Analysis, Process Improvement, Data Interpretation, Stakeholder Management, Advanced Excel, SQL, Power BI, Project Management) & 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 Mercor 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 Mercor as a Customer Success - Operations (India Region)?
Highlight Mercor's market reputation, recent tech innovations, and how your skills in Business Analysis 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.
Mercor $90 - $120 per hour
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