Data Scientist

Brillio

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

Posted 10/23/2026full-timeBangalore • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical modeling, machine learning, and data analysis to derive actionable insights. Proficient in deploying scalable models and ensuring data integrity through advanced methodologies and tools.

Highest-signal resume keywords

Statistical AnalysisMachine Learning AlgorithmsPython ProgrammingTime Series ForecastingModel Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Hypothesis TestingRegression AnalysisProbabilistic Graph ModelsClassification AlgorithmsDistance Metrics CalculationData ManipulationStatistical Analysis with SASStatistical Analysis with SPSSR ProgrammingModel Optimization

Soft Skills

CommunicationStakeholder Engagement

Tools & Technologies

TensorFlowPyTorchSci-Kit LearnCNTKKerasMXNetKubeFlowBentoMLGreat ExpectationsEvidently AI

Certifications & Qualifications

Data Science CertificationMachine Learning Certification

Industry Keywords

Data ScienceStatistical ModelingPredictive ModelingData-Driven Decision-MakingBusiness Insights

Tech Stack

Tools & technologies

KerasPySparkPythonPyTorchTensorflow

About the role

Key responsibilities & impact

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 using 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 TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
Apply 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 and translate insights into actionable recommendations that drive business outcomes

Requirements

What you’ll need

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
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
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline is listed as a desired qualification, not a requirement
Certification in Data Science or Machine Learning from a recognized institution is listed as a desired qualification, not a requirement