Time Hack Consulting Hiring Data Analyst / Analytics Engineer to work on data-driven initiatives within the fintech ecosystem. The role focuses on credit bureau analytics, lending eligibility logic, campaign analytics, customer segmentation and data pipelines.
This is a hands-on position where candidates will work with raw and unstructured datasets and convert them into Python/SQL workflows, decision rules, evaluation models and actionable business insights. The opportunity can be suitable for early-career professionals with strong analytical and programming skills.
Time Hack Consulting Hiring Data Analyst / Analytics Engineer – Overview
| Particulars | Details |
|---|---|
| Company | Time Hack Consulting |
| Job Title | Data Analyst / Analytics Engineer |
| Job Location | Not Specified |
| Experience | 0–2 Years |
| Batch | 2023, 2024, 2025 & 2026 Batch* |
| Qualification | Not Specified |
| Department | Data / Analytics |
| Employment Type | Not Specified |
| Work Mode | Not Specified |
| Key Skills | Python, SQL, Data Analytics, Fintech |
| Tools | Pandas, NumPy, Spreadsheets |
| Salary | Not Disclosed |
*The 2023–2026 batch range is a general inference from the stated 0–2 years of experience and is not an officially stated batch requirement.
About the Time Hack Consulting Data Analyst / Analytics Engineer Role
The role focuses on building data solutions from the ground up for fintech-related products. Candidates will work at the intersection of credit data, customer behavior, lending and health/financial protection offerings.
The position involves analyzing credit bureau information, developing eligibility rules, studying campaign funnels and creating data workflows for experimentation and business decision-making.
Unlike roles that primarily depend on pre-built dashboards, this position emphasizes hands-on analysis, scripting, decision logic and evaluation models.
Key Responsibilities
The selected candidate will work on:
- Analyzing raw credit bureau files.
- Working with credit scores and tradeline histories.
- Analyzing account classifications and enquiry velocity.
- Building risk segmentations.
- Developing scoring and lending eligibility rules.
- Building and maintaining Business Rule Engine (BRE) frameworks.
- Converting partner credit policies into testable code.
- Analyzing WhatsApp, voice and call-center CDR data.
- Identifying high-fit borrower segments.
- Studying conversion drivers and funnel drop-offs.
- Building algorithmic triggers based on changes in credit behavior.
- Connecting credit signals with health and financial protection offerings.
- Developing repeatable Python and SQL workflows.
- Supporting A/B testing and cohort tracking.
- Preparing performance analysis for business reviews.
- Ingesting and cleaning CRM files, call logs and bureau extracts.
- Standardizing large datasets for product and growth teams.
Eligibility
Candidates with 0–2 years of experience in Data Analytics, Data Science or a related analytical field can be considered for this opportunity.
The job description specifically mentions that internship experience is included in the experience range.
The supplied vacancy does not specify a particular degree or educational qualification. Candidates should therefore verify the latest educational requirements before applying.
Expected Batch Eligibility
Based on the stated 0–2 years of experience, this opportunity can generally be relevant to 2023, 2024, 2025 and 2026 graduates.
This is an inferred batch range and should not be treated as an official company-specified batch criterion.
SeternitySolutions Hiring Data Analyst 2026: Eligibility, Salary, Job Role & Application Details
Skills Required
Python
Strong Python knowledge is expected, particularly for working with analytical datasets using libraries such as Pandas and NumPy.
SQL
Candidates should be comfortable using SQL to extract, transform and analyze data from different sources.
Data Analytics
The role requires the ability to convert raw data into useful insights, segmentations, decision rules and performance metrics.
Statistical Understanding
Candidates should understand basic statistics, cohort dynamics and performance measurements such as:
- Precision
- Approval bands
- Conversion rates
- Cohort performance
- Funnel metrics
Spreadsheet Modeling
Spreadsheet skills are useful for rapid analysis, modelling and validating business assumptions.
Fintech & Credit Data
An interest in credit bureau data, digital lending, fintech and insurtech can be particularly valuable for this position.
Data Handling
Candidates should be comfortable working with messy, unstructured and large datasets and converting them into structured information.
Work Culture
The role appears to be suited to a hands-on, execution-focused analytics environment, where candidates are expected to build solutions rather than rely entirely on existing dashboards.
The position involves working across credit, product, growth and campaign analytics, giving analysts exposure to different business functions.
Candidates will also need to communicate technical findings to business stakeholders, making both analytical ability and clear communication important.
Because the role involves building workflows and decision logic from raw data, professionals who enjoy problem-solving, experimentation and working with unstructured information may find the environment particularly suitable.
What Should Candidates Prepare?
Python
Revise:
- Pandas
- NumPy
- Data cleaning
- Data transformation
- GroupBy operations
- Merging datasets
- Basic statistical analysis
SQL
Prepare topics such as:
- SELECT and filtering
- JOINs
- GROUP BY
- CASE statements
- Subqueries
- CTEs
- Window functions
- Aggregations
Data Analytics
Practice working with raw datasets and finding:
- Trends
- Patterns
- Outliers
- Conversion drivers
- Segment performance
- Funnel drop-offs
Statistics
Candidates should revise basic concepts related to:
- Mean, median and distribution
- Correlation
- Sampling
- A/B testing
- Precision
- Conversion rates
- Cohort analysis
Fintech & Credit Analytics
It can be helpful to understand basic concepts such as:
- Credit scores
- Tradelines
- Credit enquiries
- Risk segmentation
- Lending eligibility
- Approval rates
- Underwriting
Selection Process
The supplied job description does not mention a fixed selection process.
Candidates should be prepared for potential technical and analytical discussions involving Python, SQL, statistics, data interpretation, problem-solving and business case scenarios.
The actual selection process may vary depending on the company’s hiring requirements.
Who Can Apply?
This opportunity can be relevant for candidates who:
- Have 0–2 years of relevant analytical experience.
- Include internships as part of their practical experience.
- Have strong Python skills.
- Know SQL.
- Understand data analytics and statistics.
- Can work with messy datasets.
- Have spreadsheet modelling skills.
- Are interested in fintech and lending.
- Can translate data into business insights.
- Can communicate technical findings clearly.
- Are interested in credit analytics and decision systems.
Career Scope
Experience in this role can help candidates develop skills for careers such as:
- Data Analyst
- Analytics Engineer
- Business Analyst
- Product Analyst
- Credit Risk Analyst
- Risk Analytics Analyst
- Data Scientist
- Fintech Analytics Specialist
- Decision Science Analyst
Candidates can further strengthen their profile by learning advanced SQL, Python, machine learning, Power BI, data engineering concepts and credit risk analytics.
Frequently Asked Questions
What is the Time Hack Consulting Data Analyst role?
It is a Data Analyst / Analytics Engineer role focused on credit data, lending analytics, campaign performance, decision rules and data workflows.
What is the experience requirement?
The role requires 0–2 years of experience in Data Analytics, Data Science or a related analytical discipline, including internships.
Can freshers apply?
Yes. The experience range starts at 0 years, and internships are specifically included, making the opportunity relevant to freshers with suitable analytical skills.
Which batches can apply?
Based on the 0–2 years experience range, 2023, 2024, 2025 and 2026 batches can generally be considered. This is an inferred range rather than an officially stated batch requirement.
What technical skills are required?
The main technical requirements are Python, Pandas, NumPy, SQL and spreadsheet modelling.
Is fintech knowledge required?
The candidate profile highlights strong interest in credit bureau data, digital lending and fintech/insurtech, so domain curiosity can be valuable.
Is a degree specified?
No specific educational qualification is mentioned in the supplied job description.
What is the salary?
The supplied vacancy does not disclose the salary. Therefore, the compensation is listed as Not Disclosed.
Where is the job located?
The supplied job details do not mention a specific location.
How to Apply for Time Hack Consulting Data Analyst / Analytics Engineer
Interested candidates should review the latest vacancy details and follow the company’s official application process.
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Candidates should verify the latest eligibility, salary and vacancy status before applying.
Disclaimer: JobsMind.in is an independent career-information website and is not affiliated with Time Hack Consulting. Job details, eligibility requirements, salary, location and vacancy status may change. Candidates should verify the latest information before applying.