Senior Data Specialist – R01571898

Brillio; Pune District; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

Brillio is seeking an experienced Data Scientist with 5–8 years in advanced data science, statistical analysis, and ML to shape business outcomes. You will design models, validate data, and collaborate with cross-functional teams to translate requirements into scalable analytical solutions.

Expertise in Python, PySpark, and ML frameworks is required, along with proficiency in SAS/SPSS and probabilistic graph models. Time series forecasting and model monitoring are key focus areas.

Qualifications

• Bachelor's degree or higher in CS, Stats, Math, or Data Science.
• Certifications in Data Science, ML, or Advanced Analytics.
• Certifications in Python or R programming.

Responsibilities

• Design and implement advanced statistical models to drive business outcomes.
• Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic models.
• Build, train, and deploy predictive models using TensorFlow, PyTorch, and scikit-learn.
• Perform data cleaning, transformation, and exploratory analysis with Python, PySpark, R, SAS/SPSS.
• Apply time series forecasting methods to predict trends and inform decisions.
• Develop and maintain data validation/monitoring pipelines to ensure data quality and model performance.
• Collaborate with cross-functional teams to translate business needs into analytical solutions.
• Automate ML workflows to streamline deployment and scalability.

Skills

Hypothesis testing

Regression analysis

Python & PySpark

SAS/SPSS

Probabilistic graph models

Data validation (Great Expectations)

Time series forecasting

Classification algorithms

ML frameworks

R programming

Education

Bachelor's degree in CS/Stats/Math/Data Science

Data Science / ML certification

Python or R programming certification

Tools

Great Expectations

BentoML

KubeFlow

Evidently AI

Job description

Experience Range: With at least 5 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 8 years in related roles Key Responsibilities:

• Design and implement advanced statistical models, including hypothesis testing, regression analysis, and classification algorithms, to drive business outcomes
• Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic graph models to extract actionable insights from large datasets
• Build, train, and deploy predictive models for forecasting and classification tasks using machine learning frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn
• Perform data cleaning, transformation, and exploratory analysis utilizing Python, PySpark, R, and statistical tools like SAS or SPSS
• Apply time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to predict trends and inform strategic decisions
• Develop and maintain data validation and monitoring pipelines to ensure data quality and model performance
• Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings effectively
• Automate machine learning workflows to streamline deployment and enhance scalability

Required Skills:

• Expertise in hypothesis testing (t-test, z-test)
• Advanced regression analysis (linear and logistic)
• Programming proficiency in Python and PySpark
• Hands-on experience with SAS or SPSS for statistical computing
• Knowledge of probabilistic graph models
• Experience with data validation frameworks such as Great Expectations
• Time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
• Familiarity with classification algorithms (decision trees, SVM)
• Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn)
• Proficiency in R for statistical modeling

Preferred Skills:

• Experience with distance metrics (Hamming, Euclidean, Manhattan)
• Expertise in model monitoring tools beyond Great Expectations, such as Evidently AI
• Experience in deploying models using BentoML
• Familiarity with orchestration tools for ML workflows, such as KubeFlow
• Background in designing scalable machine learning pipelines

Desired Qualifications:

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
• Certification in Data Science, Machine Learning, or Advanced Analytics (e.g., Microsoft Certified: Azure Data Scientist Associate, SAS Certified Data Scientist)
• Certification in Python or R programming (e.g., PCEP, PCAP, R Programming Certification)