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Vrinda International

DATA SCIENTIST

Vrinda International Hyderabad, Telangana, India

Human Resources Services · 2-10 employees

13 h ago
data-scientist Principal (10+ yrs) Full-time India
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About the role

Build metrics frameworks and dashboards for digital ordering pipelines to track system performance and stability. Develop predictive models and automated anomaly detection solutions while performing statistical root-cause analysis.

What they look for

Statistics Hypothesis Testing Regression Time Series Analysis Bayesian Methods SQL Python R Scikit-learn Statsmodels Pandas NumPy AWS Tableau Anomaly Detection Predictive Modeling

Requirements

Requires over 8 years of experience in data science with strong expertise in statistics, machine learning, and SQL. Proficiency in Python or R and AWS data services is mandatory for this role.

Full description

HIRING | DATA SCIENTIST

  • Location: Hyderabad – Local Candidates Only
  • Work Mode: 4 Days WFO + 1 Day WFH
  • Experience: 8+ Years | 7+ Years Relevant
  • Budget: Up to ₹30 LPA
  • Notice Period: Immediate to 15 Days ONLY
  • Shift: 4:00 PM – 1:00 AM

? About the Role

We are looking for an experienced Data Scientist / ML Engineer with strong expertise in statistical modeling, advanced analytics, machine learning, SQL, Python and AWS data services.

? Mandatory Skills

✅ Strong foundation in Statistics

✅ Hypothesis Testing, Regression, Time Series Analysis & Bayesian Methods

✅ Advanced SQL

✅ Python / R

✅ Scikit-learn, Statsmodels, Pandas & NumPy

✅ AWS – SageMaker, Redshift, Athena, Glue, QuickSight or similar

✅ Hands-on Tableau experience

✅ Metrics framework & dashboard development from scratch

✅ Anomaly Detection & Predictive Modeling

✅ Experience working with data from multiple systems

✅ Strong communication & stakeholder management skills

? Key Responsibilities

  • Build metrics frameworks for digital ordering pipelines
  • Develop dashboards for volume, throughput, TAT, errors and system stability
  • Build predictive models for failures, trends and capacity planning
  • Develop automated anomaly detection solutions
  • Perform statistical root-cause analysis
  • Partner with engineering teams for data instrumentation
  • Present technical/statistical insights to leadership and engineering teams
  • Analyze production issues and quantify business impact

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