Data Scientist - R01570830

Brillio; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

Brillio is seeking a Data Scientist in Bengaluru to develop and deploy advanced data science solutions. You will work on Next Best Offer models, probabilistic graphs, and ensemble methods to drive customer engagement and business outcomes.

The role emphasizes building, validating, and monitoring ML models with Python, PySpark, and R, while leveraging KubeFlow and BentoML for scalable deployment. Strong statistical background is essential.

Qualifications

• Experience Range: With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline
• Certification in Machine Learning or Data Science from Coursera, edX, or DataCamp
• Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst

Responsibilities

• Develop and implement Next Best Offer models and advanced data science solutions to drive business objectives and enhance customer engagement
• Apply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-making
• Build, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliability
• Leverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challenges
• Optimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiency
• Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategies
• Monitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectiveness
• Collaborate with cross-functional teams to translate business requirements into impactful data science solutions

Skills

Python

PySpark

SAS

SPSS

R

Probabilistic graph models

Regression methods

Forecasting methods

TensorFlow

PyTorch

Scikit-learn

CNTK

Keras

MXNet

Decision trees

Support Vector Machines

Distance metrics

KubeFlow

BentoML

Education

Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline

Certification in Machine Learning or Data Science (Coursera, edX, or DataCamp)

Certification in statistical analysis or analytics (e.g., SAS Certified Statistical Business Analyst)

Tools

KubeFlow

BentoML

Job description

Data Scientist

Job requirements

Experience Range: With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects

Key Responsibilities

• Develop and implement Next Best Offer models and advanced data science solutions to drive business objectives and enhance customer engagement
• Apply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-making
• Build, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliability
• Leverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challenges
• Optimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiency
• Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategies
• Monitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectiveness
• Collaborate with cross-functional teams to translate business requirements into impactful data science solutions

Required Skills

• Python
• PySpark
• SAS
• SPSS
• R
• Probabilistic graph models
• Regression methods (linear and logistic)
• Forecasting methods (exponential smoothing, ARIMA, ARIMAX)
• TensorFlow
• PyTorch
• Scikit-learn
• CNTK
• Keras
• MXNet
• Decision trees
• Support Vector Machines (SVM)
• Distance metrics (Hamming, Euclidean, Manhattan)
• KubeFlow
• BentoML

Preferred Skills

• Experience with Great Expectations and Evidently AI for model validation and monitoring
• Expertise in deploying machine learning models in cloud-based environments
• Knowledge of advanced ensemble methods and boosting algorithms
• Familiarity with A/B testing and experimental design
• Background in recommendation systems and personalization algorithms

Desired Qualifications

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline relevant to data science
• Certification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCamp
• Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst