Data Scientist

Systems-Plus; Pune District; On-site; INR 800,000 - 1,500,000; Full time

Job summary

Systems-Plus is hiring a Data Scientist in Pune. The ideal candidate will leverage statistical modeling and machine learning to deliver insights and support data-driven decision-making across the organization.

Responsibilities include building machine learning models, conducting statistical analyses, and providing actionable insights to stakeholders. A Bachelor's or Master’s degree in a related field along with 3–7+ years of experience is required. Strong skills in Python and SQL are essential.

Qualifications

• 3–7+ years of experience applying data science techniques in a business environment.
• Proficiency in Python (pandas, scikit‑learn, 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.

Responsibilities

• Build, validate, and deploy machine learning models (classification, regression, forecasting, clustering, NLP, etc.).
• Acquire, clean, and manipulate large datasets from multiple sources.
• Deliver clear, actionable insights to stakeholders through ad‑hoc analysis, dashboards, and visualizations.

Skills

Statistical modeling

Machine learning

Python

SQL

Data analysis

Data visualization

Experiment design

Education

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field

Tools

Python libraries (pandas, scikit‑learn, NumPy, statsmodels)

Big data tools (Spark, Databricks, Snowflake, BigQuery, Redshift)

Cloud platforms (Snowflake, Azure, AWS, GCP)

Dashboard tools (Power BI, Tableau)

Job description

HIRING www.systems-plus.com

Data Scientist

Location: Pune
Employment Type: full-time
Designation: Data Scientist

Job Details

Job Title: Data Scientist

Overview

We are seeking a highly skilled Data Scientist to join our marketing analytics organization. In this role, you will leverage statistical modeling, machine learning, and data engineering techniques to deliver insights, build predictive models, and support data‑driven decision‑making across the business through 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 deploy machine learning models (classification, regression, forecasting, clustering, NLP, etc.)
• Conduct statistical analyses and 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, and Snowflake.
• Work closely with data engineers to optimize data structures and improve data availability.

Insights & Business Impact (40%)

• Deliver clear, actionable insights to stakeholders through ad‑hoc analysis, dashboards, visualizations, and written summaries.
• Partner with product, marketing, finance, and operations teams to identify opportunities 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

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• 3–7+ years of experience applying data science techniques in a business environment.
• Proficiency in Python (pandas, scikit‑learn, 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 with machine learning, feature engineering, and model evaluation.
• Ability to communicate complex concepts to non‑technical audiences.
• Ability to perform ad‑hoc analysis for LOBs.

Preferred Qualifications

• Experience with cloud platforms such as Snowflake, Azure, AWS, or GCP.
• Experience with big data tools (Spark, Databricks, Snowflake, BigQuery, Redshift).
• Experience with deep learning (PyTorch, TensorFlow) or NLP.
• 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

• Strong problem‑solving and critical‑thinking skills.
• Comfort working in fast‑paced, ambiguous environments.
• Curiosity and a continuous learning mindset.

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