Data Science Engineer

Tekskills Inc.; Mumbai; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Tekskills Inc. is seeking a Senior Data Analyst / Data Science Engineer for a Gurgaon-based role with 7-9 years of experience in Python-based analytics and statistical modelling. The role emphasizes converting complex Excel models into Python and deploying reusable pipelines with tests and documentation.

You will work with stakeholders to discuss model assumptions, ensure data quality, and implement production-ready code with robust data wrangling and regression analyses.

Qualifications

• 7+ years of handson experience in Python-based analytics and statistical modelling (regression, forecasting, GLM).
• Convert complex Excel models into Python and deploy as reusable pipelines.
• Strong data wrangling and SQL proficiency for data extraction and quality.

Responsibilities

• Convert Excel models into Python with production-ready code and tests.
• Discuss model assumptions with business stakeholders and implement robust solutions.

Skills

Python

pandas

numpy

statsmodels

scikit-learn

data wrangling

regression

Excel to Python

SQL

Git

Tools

SQL

Git

Job description

Role: Senior Data Analyst / Data Science Engineer
Level: Senior (7-9 years)
Location: Gurgaon

7+ years of handson experience in Python-based analytics, statistical modelling (regression, forecasting, GLM), and strong data wrangling. You will convert complex Excel models into Python, validate parity, enhance them with software engineering best practices, and deploy them as reusable components/pipelines. The ideal candidate is equally comfortable discussing model assumptions with business stakeholders and implementing productionready code with tests and documentation.

Musthave qualifications

• 710 years in analytics/data science with demonstrable Python proficiency (pandas, numpy, statsmodels, scikitlearn).
• Strong command of regression techniques (linear, logistic, regularization, model diagnostics, crossvalidation).
• Proven experience converting Excel models into Python (e.g., complex formulas, lookups, macros/VBA logic translated to Pythonic pipelines).
• SQL proficiency for data extraction and joins; solid EDA and data quality practices.
• Clear, structured communication; stakeholder management and requirement grooming.
• Version control (Git), notebook hygiene, and documentation habits.