Senior Data Specialist

Brillio; Pune District; On-site; INR 900,000 - 1,350,000; Full time

Job summary

Brillio in Pune, India, seeks a Senior Data Specialist to lead advanced data science initiatives. The role focuses on statistical modeling, ML deployment, and data quality assurance within cross-functional projects.

Ideal candidates have 5–8 years of experience in statistics, ML, and data analytics, with proficiency in Python, PySpark, SAS/SPSS and modern ML frameworks. Immediate joiner preferred, with strong communication skills and stakeholder collaboration.

Qualifications

• Candidates must have hands-on experience in advanced data science and ML.
• Proven ability to design statistical models and deploy ML solutions.
• Strong background in time series, regression, and hypothesis testing.

Responsibilities

• Design and implement advanced statistical models to drive business outcomes.
• Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic graphs.
• Build, train, and deploy predictive models with ML frameworks like TensorFlow, PyTorch, and scikit-learn.
• Clean, transform, and explore data using Python, PySpark, R, SAS or SPSS.
• Apply time series methods to forecast trends and inform decisions.
• Develop data validation and monitoring pipelines to ensure quality and performance.
• Collaborate with cross-functional teams to translate requirements into analytics.
• Automate ML workflows to improve deployment and scalability.

Skills

Hypothesis testing

Regression analysis

Python

PySpark

SAS/SPSS

Probabilistic graphs

Great Expectations

Time series forecasting

Classification (DT/SVM)

ML frameworks (TF, PyTorch, scikit-le-

R programming

Education

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

Certifications in DS/ML/Advanced Analytics

Python or R programming certification

Tools

Great Expectations

Evidently AI

BentoML

KubeFlow

Job description

Senior Data Specialist

Job Requirements

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

• Bachelors 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)

Additional Information

Immediate joiner required

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.