Website Time Hack Consulting

Data Analyst / Analytics Engineer – Time Hack Consulting

Client Sector: High-Growth Fintech & Insurtech Platform
Role Level: Entry-Level / Junior (0–2 Years Experience; Internships Included)
Employment Type: Full-Time
Industry: Digital Lending, Credit Intelligence & Health Memberships
Core Tech Stack: Python (pandas, numpy), SQL, Business Rule Engines (BRE), Credit Bureau Data Parsing, Cohort Analysis

About the Role & Client Context

Time Hack Consulting is recruiting a hands-on Data Analyst / Analytics Engineer for a high-growth fintech platform. The client is actively scaling two core business lines:
  1. A credit bureau intelligence engine that transforms financial signals into automated lending underwriting rules.
  2. An embedded health membership product integrated into its core lending distribution funnel.
This is a build-from-scratch role requiring direct manipulation of raw data, custom Python/SQL scripting, and rule-engine logic design without relying on pre-built dashboards.

Key Responsibilities

  • Credit Bureau Intelligence: Clean, parse, and analyze raw bureau files (credit scores, tradeline histories, account classifications, enquiry velocity) to define risk segments and eligibility logic.
  • Business Rule Engine (BRE) Development: Translate lending partner policies into client-side Business Rule Engines and testable programmatic logic.
  • Funnel & Campaign Analytics: Analyze multi-channel communication logs (WhatsApp, voice, CDR call data) to identify borrower segments, optimize conversion funnels, and reduce drop-offs.
  • Signal-to-Trigger Mapping: Build algorithmic triggers that connect credit behavior shifts to contextual financial protection and health offerings.
  • Pipeline & Experimentation: Build repeatable Python and SQL workflows for A/B testing, cohort tracking, conversion performance modeling, and executive reviews.
  • Data Structuring & Cleaning: Ingest and standardize unstructured CRM files, call center logs, and raw bureau extracts for growth and product engineering teams.

Candidate Profile & Requirements

  • Experience: 0–2 years in Data Analytics, Data Engineering, or Data Science (relevant internships and personal/academic projects accepted).
  • Technical Stack:
    • Python: Strong hands-on data manipulation skills using pandas and numpy.
    • Database Querying: Advanced SQL capabilities for joining, filtering, and aggregating transactional datasets.
    • Spreadsheet Modeling: Rapid prototyping and logic validation in Excel or Google Sheets.
  • Analytical Foundation: Practical understanding of statistics, cohort analysis, and performance metrics (Precision, Approval Bands, Conversion Rates, LTV/CAC).
  • Domain Interest: High curiosity for credit bureau mechanics, digital lending funnels, and embedded insurtech products.
  • Nice to Have:
    • Basic exposure to classification ML models or logistic regression.
    • Lightweight UI development (HTML/JavaScript) for internal tools or scripts.
    • Prior exposure to lending, credit risk, or insurance underwriting logic.

Role Summary

Attribute Details
Job Title Data Analyst / Analytics Engineer
Recruiting Firm Time Hack Consulting
Domain Fintech, Digital Lending & Embedded Insurtech
Experience Required 0–2 Years (Freshers & Interns Eligible)
Focus Area Bureau Intelligence, BRE Rule Design, Funnel Analytics
Core Stack Python (pandas, numpy), SQL, Credit Bureau Data, Cohort Analysis

To apply for this job please visit remotejobhiring.com.