Hiring Data Analyst

Hiring Data Analyst !

Company: Mechademy
Location: Gurugram
Work Mode: Hybrid
Experience: 1-3 years

About Mechademy
Mechademy builds an enterprise AI platform for real-time monitoring, diagnostics, and predictive maintenance of industrial equipment. We are a venture-funded, Series A startup experiencing 8090% YoY growth, with 15+ enterprise clients across oil & gas, power generation, and LNG.

The Opportunity
We are looking for a sharp Data Analyst who thrives on open-ended problem-solving. Instead of answering pre-packaged questions or staring at standing dashboards, you will be handed raw data and complex industrial datasets (sensor streams across speed, pressure, temperature, flow, and vibration) to figure out what is actually happening. Your findings will directly inform engineers making decisions on assets worth hundreds of millions of dollars.

What You'll Own

Investigation & Root Cause (40%): Pull and structure raw sensor data across time windows, formulate testable hypotheses, and work alongside domain engineers to trace anomalies from raw signals to defensible recommendations.
Performance & Efficiency (25%): Analyze relationships between operating variables, build before/after intervention studies, and derive performance metrics to quantify asset degradation or improvement.
Reporting & Communication (15%): Produce clear visualizations, structured analytical reports, and summaries that stand up to leadership scrutiny.
Product Analytics (10%): Analyze internal user interactions and platform usage metrics to help improve the Mechademy product itself.
Knowledge & Reuse (10%): Document analytical patterns and help build a shared knowledge base of equipment behavior and reusable frameworks.

Who You Are (Must-Haves)
Structured Problem-Solving: Ability to break down vague, large-scale problems into solvable components and stitch them back into coherent answers.
Defensible Reasoning: Your conclusions logically follow from your analysis, and you can clearly walk senior stakeholders through your work.
Python Proficiency: Daily comfort with Python (pandas, numpy, and basic scipy for statistical checks) as a core analytical tool.
Time-Series Experience: Comfort working with sequential data indexed over time, spotting trends, seasonality, and drift.
Hypothesis-Driven Mindset: A natural reflex to form testable explanations when encountering anomalies rather than random searching.
Comfort with Ambiguity: Ability to take a vague prompt and turn it into a rigorous, structured investigation.

Strong Signals
Exposure to real equipment, IoT, SCADA, or industrial sensor streams.
Curiosity about product and user behavior analytics.
Engineering, science, or quantitative academic background.