Data Scientist

Systems Plus; Pune District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Systems Plus is seeking a Data Scientist to join its marketing analytics team. You will leverage statistical modeling, ML, and data engineering to deliver insights, build predictive models, and support data-driven decision making across the business.

The role focuses on analytics, data prep, and delivering actionable insights to product, marketing, finance, and operations teams while collaborating with engineering for model deployment and monitoring.

Qualifications

• Bachelor’s/Master’s degree in a relevant field with strong analytical foundation.
• 3–7+ years applying data science techniques in business environments.
• Proficiency in Python (pandas, scikit-learn, NumPy) and SQL.

Responsibilities

• Build, validate, and deploy ML models (classification, regression, forecasting, clustering, NLP).
• Conduct statistical analyses and A/B tests to evaluate performance.
• Translate business questions into structured analytical problems for insights.

Skills

Data Science

Python

SQL

Machine Learning

Data Visualization

Communication

Ad-hoc Analysis

Education

Master's in Data Science/Statistics/CS

Tools

Snowflake

Spark

TensorFlow

Power BI

Tableau

Job description

Job Title: Data Scientist

Overview

We areseekinga highly skilledData Scientistto join ourmarketinganalytics organization. In this role, you willleveragestatistical modeling, machine learning, and data engineering techniques to deliver insights, build predictive models, and supportdatadrivendecisionmakingacross the businessconducting ad-hoc analysis.The ideal candidate is analytically strong, curious, and comfortable working with large datasets and modern data technologies.

Key Responsibilities

Analytics & Modeling(40%)

• Build,validate, and deploymachine learning models(classification, regression, forecasting, clustering, NLP, etc.)
• Conductstatistical analysesand A/B tests to evaluate business performance and product changes.
• Translate ambiguous business questions into structured analytical problems.

Data Engineering & Preparation(10%)

• Acquire, clean, and manipulate large datasets from multiple sources.
• Build reproducible data pipelines using Python, SQL, andSnowflake.
• Work closely with data engineers tooptimizedata structures and improve data availability.

Insights & Business Impact(40%)

• Deliver clear, actionable insights to stakeholders throughah-hoc analysis,dashboards, visualizations, and written summaries.
• Partner with product, marketing, finance, and operations teams toidentifyopportunities for optimization.
• Support KPI development and help teams understand business trends.

Model Deployment & Monitoring(10%)

• Collaborate with engineering teams to deploy models into production environments.
• Monitor model performance and retrain/adjust, as necessary.
• Maintain documentation, reproducibility, and version control of all modeling work.

Required Skills & Qualifications

• Bachelors orMaster’s degree inData Science, Statistics, Computer Science, Mathematics, ora relatedfield.
• 3–7+ years of experience applying data science techniques in a business environment.
• ProficiencyinPython(pandas,scikitlearn, NumPy,statsmodels)or other model building tools.
• Strong SQL skills and experience with relational or cloud databases.
• Deep understanding of statistical modeling, hypothesis testing, and experiment design.
• Experience withmachine learning, feature engineering, and model evaluation.
• Ability to communicate complex concepts tonontechnicalaudiences.
• Ability to perform ad-hoc analysis for LOBs.

Preferred Qualifications

• Experience withcloud platformssuch asSnowflake,Azure, AWS, or GCP.
• Experience withbig data tools(Spark, Databricks, Snowflake,BigQuery, Redshift).
• Experience withdeep learning(PyTorch, TensorFlow) orNLP.
• Experience building dashboards in Power BI, Tableau, or similar tools.
• Experience as a data analyst conducting ad-hoc analysis.
• Knowledge of data governance and model lifecycle best practices.

Soft Skills

• Strongproblemsolvingandcriticalthinkingskills.
• Comfort working infast paced, ambiguous environments.
• Curiosity and a continuous learning mindset.