Data Scientist - R01571773

Brillio 2

Pune District

On-site

INR 1,400,000 - 2,100,000

Full time

2 days ago
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Job summary

Brillio 2 is seeking a Data Scientist with at least 4 years of experience in advanced data science, statistical analysis, and ML model development. You will work with large datasets, implement models in production, and collaborate across teams to translate business needs into analytical solutions.

The role emphasizes Python, PySpark, and ML frameworks, with deployment and monitoring of models in cloud and production environments, and the use of data validation tools.

Qualifications

  • At least 4 years of experience in advanced data science and ML model development.
  • Experience with large datasets and production model deployment.
  • Proficient in Python, R, and ML frameworks.

Responsibilities

  • Design, develop, and deploy ML models using Python, R, and frameworks to address complex business challenges.
  • Conduct rigorous statistical analyses, including hypothesis testing and probabilistic modeling, to extract insights from large-scale data.
  • Implement data quality checks using tools such as Great Expectations and Evidently AI to ensure data and model integrity.
  • Collaborate with cross-functional teams to translate business requirements into analytical solutions and present findings.
  • Develop, optimize, and maintain forecasting models using exponential smoothing, ARIMA, and ARIMAX.
  • Build, train, and evaluate classification and regression models using ML frameworks (TensorFlow, PyTorch, scikit-learn, Keras, MXNet).
  • Deploy and monitor models in production environments using scalable cloud-native tools such as KubeFlow and BentoML.
  • Document methodologies and contribute to continuous improvement of analytics best practices.

Skills

Python
PySpark
Statistical analysis
ML model development
Hypothesis testing
Data visualization
Production deployment
Collaboration

Education

Bachelor's in CS/Statistics/Data Science

Tools

TensorFlow
PyTorch
scikit-learn
Keras
Great Expectations
Evidently AI

Job description

Data Scientist
Experience Range:

With at least 4 years of experience in advanced data science, statistical analysis, and machine learning model development, including hands-on work with large datasets and production model deployment.

Key Responsibilities:
  • Design, develop, and deploy advanced statistical and machine learning models using Python, R, and specialized frameworks to address complex business challenges
  • Conduct rigorous statistical analysis, including hypothesis testing, regression analysis, and probabilistic modeling, to extract actionable insights from large-scale data
  • Implement and validate data quality checks using tools such as Great Expectations and Evidently AI to ensure data and model integrity
  • Collaborate with cross-functional teams to define data-driven strategies, translate business requirements into analytical solutions, and present findings to stakeholders
  • Develop, optimize, and maintain forecasting models using techniques such as exponential smoothing, ARIMA, and ARIMAX to support business planning
  • Build, train, and evaluate classification and regression models using ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras, MXNet, CNTK)
  • Deploy and monitor models in production environments using scalable cloud-native tools such as KubeFlow and BentoML
  • Document methodologies and contribute to continuous improvement of analytics best practices
Required Skills:
  • Advanced proficiency in Python and PySpark for data analysis and model development
  • Expertise in statistical analysis and computing using SAS or SPSS
  • Hands-on experience with regression techniques including linear and logistic regression
  • Strong knowledge of hypothesis testing, including T-Test and Z-Test methodologies
  • Proficient in building and interpreting probabilistic graphical models
  • Experience with classification algorithms such as Decision Trees and Support Vector Machines (SVM)
  • Skilled in forecasting techniques including exponential smoothing, ARIMA, and ARIMAX
  • Familiarity with distance metrics such as Hamming, Euclidean, and Manhattan Distance
  • Working knowledge of R and R Studio for statistical modeling
  • Experience with data validation and monitoring tools such as Great Expectations and Evidently AI
Preferred Skills:
  • Experience deploying machine learning models using KubeFlow or BentoML
  • Proficiency with deep learning frameworks such as TensorFlow, PyTorch, Keras, MXNet, or CNTK
  • Background in cloud-based analytics platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform)
  • Exposure to automated machine learning (AutoML) workflows
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 provider (e.g., Microsoft Certified: Azure Data Scientist Associate, IBM Data Science Professional Certificate)
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