Data Scientist

Company: KG Invicta Services Pvt Ltd

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Enterprise

Company Type: Product & Service

Business Model: B2B

Funding Stage: Private Equity

Industry: Healthcare IT

Salary Range: ₹ 25-32 Lacs PA

Job Description

JOB DESCRIPTION

Job Summary

We are seeking a Data Analyst / Data Scientist with strong big data experience to analyze large heterogeneous datasets, build statistical and ML models, and deliver actionable insights and dashboards. The role emphasizes analytics, modeling, and stakeholder-facing reporting while collaborating with data engineers for data access and pipeline needs.

Key Responsibilities

• Analyze large-scale datasets to identify trends, drivers, anomalies, and business opportunities.
• Design, develop, validate, and deploy statistical models and machine-learning solutions to solve business and clinical problems.
• Prepare, clean, transform, and model data for analysis in collaboration with data engineering teams.
• Build interactive dashboards, visualizations, and automated reports to support decision-making.
• Conduct exploratory data analysis, A/B testing, cohort analyses, and predictive analytics.
• Translate analytical findings into clear, actionable recommendations and present to stakeholders.
• Ensure reproducibility by maintaining notebooks, pipelines, model artifacts, and documentation.
• Implement monitoring for model performance and work with engineers to operationalize models.
• Uphold data governance, privacy, and security standards for sensitive healthcare data.

Qualification And Experience

• Bachelor’s or Master’s in Data Science, Statistics, Computer Science, Engineering, or related field.
• 5+ years of experience in data analysis, applied statistics, or data science on large datasets.
• Experience working with healthcare data is preferred.

Technical Skills

• Strong SQL and Python; R acceptable.
• Experience with big data frameworks and querying large datasets.
• Familiarity with data engineering tools (Azure Data Factory, ETL concepts) to collaborate effectively.
• Experience building dashboards in Power BI or Tableau.
• Experience with model validation, feature engineering, and ML lifecycle (training, evaluation, deployment).

Knowledge of statistical testing, regression, time-series, clustering, and classification techniques.