Data Scientist – R01572016

Brillio; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Brillio is seeking an experienced data scientist in Pune with 4–6 years of hands-on experience in advanced data science, statistics, and machine learning. The role emphasizes robust modeling, predictive analytics, and data-driven business insights.

You will design and deploy models using Python, PySpark, and R, validate with SAS/SPSS, and present findings to stakeholders. Opportunity to work with leading ML frameworks and cloud deployments in a collaborative team.

Qualifications

• 4–6 years of hands-on data science experience including statistical analysis and ML
• Proficient in Python, PySpark, and R for data manipulation and modeling
• Strong experience with SAS, SPSS, and R Studio for statistical analysis

Responsibilities

• Design and implement statistical models using hypothesis testing, regression, and forecasting
• Develop and optimize ML algorithms for classification, prediction, and probabilistic graphs with Python, PySpark, and R
• Conduct statistical analyses with SAS, SPSS, and R Studio to support data-driven decisions
• Build, train, and deploy scalable models using TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet
• Apply time series forecasting methods (exponential smoothing, ARIMA, ARIMAX) to predict trends
• Streamline model deployment and lifecycle management in production with KubeFlow and BentoML
• Implement data quality checks with Great Expectations and Evidently AI to ensure dataset integrity
• Present insights to stakeholders, translating them into actionable business recommendations

Skills

Hypothesis testing

Regression analysis

Python

PySpark

R

SAS

SPSS

Time series forecasting

ML algorithms

Classification algorithms

SVM

Decision trees

R Studio

Model deployment

Education

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science

Certification in Data Science or Machine Learning

Tools

TensorFlow

PyTorch

Sci-Kit Learn

CNTK

Keras

MXNet

Great Expectations

Evidently AI

KubeFlow

BentoML

Job description

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