Live opening · Posted 5 days ago

Senior Data Scientist- R & Statistical Modelling

Haparz · Pune Division, Maharashtra, India (Hybrid)
Linkedin Hybrid
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyHaparz
LocationPune Division, Maharashtra, India (Hybrid)
Work modeHybrid
SourceLinkedin
Listed5 days ago

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About the role

Description supplied by the original job listing.

NO FRESHER WILL BE PREFERRED
We are looking for Senior Data Scientist - R & Stastical Modelling Case Management as a Full Time for our IT Company.
Location- Pune
Experience- 6+ years
Budget- As per company standard
Notice Period- Immediate Joiner
About the role:
We are looking for a highly skilled Senior Data Scientist to take ownership of our core analytical models. In this pivotal role, you will dive deeply into our existing suite of algorithms written in R, conducting rigorous statistical analysis to understand, validate, and optimize their performance. You won't just be maintaining legacy code; you will be the driving force behind enhancing our current methodologies and architecting brand-new features and predictive models that solve complex business challenges.
Responsibilities:
- Algorithm Ownership & Reverse Engineering: Analyze, deconstruct, and thoroughly map out complex existing statistical models and algorithms written in R
- Rigorous Statistical Analysis: Conduct deep-dive statistical testing on current models to identify areas for performance improvement, accuracy optimization, and efficiency gains
- Continuous Enhancement: Design and implement robust solutions to modernize and enhance existing functionality, ensuring our models scale effectively with growing data
- Feature Engineering & Development: Conceptualize, build, and deploy new analytical features and models from scratch to support emerging product and business needs
- Production & Code Quality: Refactor and upgrade existing R code into robust, production-ready frameworks. Champion best practices for version control, code documentation, and automated testing
- Cross-Functional Collaboration: Partner with Data Engineering to streamline model deployment and translate complex statistical outcomes into actionable insights for non-technical stakeholders
- Mentorship: Guide and mentor junior data scientists and analysts, fostering a culture of technical excellence and continuous learning
Requirements:
- Education: Master's or Ph.D. in Statistics, Applied Mathematics, Computer Science, Data Science, or a closely related quantitative discipline
- Experience: 5+ years of hands-on professional experience in data science, statistical modeling, or quantitative research
- Technical Mastery in R: Expert-level proficiency in R programming. You should be highly comfortable with the tidyverse, data.table, and various advanced statistical/modeling packages
- Statistical Depth: Deep practical knowledge of applied statistics (e.g., hypothesis testing, linear/logistic regression, time-series analysis, mixed-effects models, or Bayesian methods)
- Analytical Problem-Solving: Proven track record of auditing existing codebases, identifying bottlenecks, and successfully implementing measurable algorithmic enhancements
- Communication: Exceptional ability to document complex algorithms clearly and explain highly technical concepts to executive leadership
Desirable:
- Experience with building APIs in R (e.g., plumber) or developing interactive dashboards (e.g., Shiny)
- Familiarity with containerizing R applications (Docker) and deploying models in cloud environments (AWS, GCP, Azure)
- Working knowledge of Python (pandas, scikit-learn) or SQL to effectively collaborate with broader engineering teams
- Domain expertise in Banking or Financial Services

Work arrangement
Hybrid

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