Data Science Engineer

Tekskills Inc.; Kolkata District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Tekskills Inc. is seeking a Senior Data Analyst / Data Science Engineer in Gurgaon. You will leverage 7+ years of hands-on Python-based analytics, build statistical models, and wrangle large datasets to convert complex Excel models into robust Python pipelines.

You will discuss model assumptions with business stakeholders, implement production-ready code with tests and documentation, and ensure repeatable, well-documented deliverables across the analytics stack.

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.

Responsibilities

• Convert complex Excel models into Python and deploy as reusable pipelines.
• Validate parity and enhance models with software engineering best practices.
• Discuss model assumptions with business stakeholders and implement production-ready code with tests and documentation.

Skills

Python analytics

Statistical modelling

Data wrangling

Excel to Python conversion

SQL

EDA and data quality

Git

Notebook hygiene

Stakeholder communication

Tools

Git

Jupyter

Pandas

NumPy

Statsmodels

scikit-learn

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.