Data Science Engineer

Tekskills Inc.; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Tekskills Inc. seeks a Senior Data Analyst / Data Science Engineer with 7+ years in Python-based analytics to join the Gurgaon team. You will convert complex Excel models into Python, validate parity, and deploy reusable data pipelines with tests and documentation.

The ideal candidate excels at regression modelling, data wrangling, and engaging with business stakeholders to discuss model assumptions and deliver production-ready solutions.

Qualifications

• 7+ years of hands-on analytics with Python.
• Strong regression and model diagnostics knowledge.
• Experience converting complex Excel models to Python pipelines.
• Proficiency with SQL for data extraction and joins.
• Excellent communication and stakeholder grooming.

Responsibilities

• Translate Excel-based models into Python pipelines.
• Validate parity between original and Python models.
• Deploy reusable components with tests and documentation.
• Engage with stakeholders to discuss model assumptions and requirements.

Skills

Python

Pandas

NumPy

Statsmodels

Scikit-learn

Regression techniques

Excel to Python

Data Wrangling

Git

Communication

Stakeholder management

Tools

SQL

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.