# Data Scientist - R01572015 at Brillio

Data Scientist - R01572015 at Brillio in Pune, Maharashtra, India. Hybrid. Posted September 29, 2026.

- Company: Brillio
- Location: Pune, Maharashtra, India
- Workplace: Hybrid
- Posted: 2026-09-29
- Apply: https://jobs.lever.co/brillio-2/265bed8f-1d77-462c-b7ab-b82c4b129bd0/apply
- Source: https://jobmagic.ai/jobs/data-scientist-r01572015-brillio-azt6bj

## Requirements

- Design and implement robust statistical models using advanced hypothesis testing, regression, and forecasting techniques to deliver actionable business insights
- Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models utilizing Python, PySpark, and R
- Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making
- Build, train, and deploy scalable models using ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
- Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to analyze trends and predict outcomes
- Streamline model deployment and lifecycle management in production environments using KubeFlow and BentoML
- Implement and validate data quality checks with Great Expectations and Evidently AI to ensure dataset integrity
- Present complex data findings to stakeholders, translating insights into actionable recommendations that drive business outcomes
- Advanced application of hypothesis testing methodologies, including T-Test and Z-Test
- Expert-level regression analysis (linear and logistic) for predictive modeling
- Proficient programming in Python and PySpark for data manipulation and model development
- Extensive experience with statistical analysis using SAS and SPSS
- Hands-on expertise in probabilistic graph models for complex data relationships
- Mastery of time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
- Implementation of classification algorithms such as decision trees and support vector machines (SVM)

## Description

**Data Scientist**

### Job requirements

**Experience Range:** With at least 4 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 6 years in similar roles **Key Responsibilities:**

- Design and implement robust statistical models using advanced hypothesis testing, regression, and forecasting techniques to deliver actionable business insights

- Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models utilizing Python, PySpark, and R

- Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making

- Build, train, and deploy scalable models using ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet

- Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to analyze trends and predict outcomes

- Streamline model deployment and lifecycle management in production environments using KubeFlow and BentoML

- Implement and validate data quality checks with Great Expectations and Evidently AI to ensure dataset integrity

- Present complex data findings to stakeholders, translating insights into actionable recommendations that drive business outcomes

**Required Skills:**

- Advanced application of hypothesis testing methodologies, including T-Test and Z-Test

- Expert-level regression analysis (linear and logistic) for predictive modeling

- Proficient programming in Python and PySpark for data manipulation and model development

- Extensive experience with statistical analysis using SAS and SPSS

- Hands-on expertise in probabilistic graph models for complex data relationships

- Mastery of time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)

- Implementation of classification algorithms such as decision trees and support vector machines (SVM)

- Deep familiarity with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet

- Calculation and application of distance metrics (Hamming, Euclidean, Manhattan)

- Skilled in R and R Studio for statistical analysis and visualization

**Preferred Skills:**

- Practical experience with Great Expectations and Evidently AI for advanced data validation

- Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML

- Background in large-scale data processing and distributed computing environments

- Expertise in feature engineering and model interpretability techniques

- Familiarity with cloud-based data science platforms such as AWS SageMaker, Azure ML, or Google Cloud AI Platform

**Desired Qualifications:**

- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline

- Certification in Data Science or Machine Learning from a recognized institution, such as Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate