Time since we first saw it
Day 36
Similar jobs usually come down between day 7 and day 56.
At Brillio-2, jobs usually come down by about day 25.
From 10,319 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.
Data Scientist
Pune, Maharashtra, India
Live, first seen by us 36 days ago- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDesign and implement statistical models for business insights
Develop machine learning models for classification and prediction
Build and deploy scalable models into production environments
Apply time series forecasting methods to trends and outcomes
Present data findings and recommendations to stakeholders
From the employer’s posting
Design and implement robust statistical models using advanced hypothesis testing, regression, and forecasting techniques
Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models
Build, train, and deploy scalable models using ML frameworks
Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX
Present complex data findings to stakeholders, translating insights into actionable recommendations
What you’ll bring
All qualificationsCore experience
- At least 4 years of hands-on data science experience
- Expert regression analysis (linear and logistic)
- Proficiency in Python and PySpark
- Experience with SAS and SPSS statistical analysis
- Skill in R and R Studio for statistics and visualization
Preferred experience
- Practical experience with Great Expectations and Evidently AI for advanced data validation
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
- Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML
- Expertise in feature engineering and model interpretability techniques
Qualification wording
With at least 4 years of hands-on experience in advanced data science
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
Skilled in R and R Studio for statistical analysis and visualization
Practical experience with Great Expectations and Evidently AI for advanced data validation
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML
Expertise in feature engineering and model interpretability techniques
Education & alternatives
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 institution, such as Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 30, 202636 days ago
- Recorded sightings
- 87
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Brillio-2 is hiring
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring has slowed
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- R
- SAS
- AWS
- Azure
- SageMaker
- Keras
- PySpark
- PyTorch
- TensorFlow
- GCP
- Great Expectations
Where the posting names them
- 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 utilizing Python, PySpark, and R - Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making
- 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
- Develop and optimize machine learning algorithms for classification, prediction, and probabilistic graph models utilizing 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 ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
- Calculation and application of distance metrics (Hamming, Euclidean, Manhattan) - Skilled in R and R Studio for statistical analysis and visualization Preferred Skills:
- 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
- Expertise in feature engineering and model interpretability techniques - Familiarity with cloud-based data science platforms such as AWS SageMaker, Azure ML, or Google Cloud AI Platform 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 institution, such as Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate Employment type
- Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to support data-driven decision-making - Build, train, and deploy scalable models using ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet - Apply advanced time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to analyze trends and predict outcomes
- 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)
- 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, translating insights into actionable recommendations that drive business outcomes
Preferred Skills: - Practical experience with Great Expectations and Evidently AI for advanced data validation - Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML
Your next step
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Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Data Scientist
Job requirements
- 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 utilizing 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 ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
- Apply advanced 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, translating insights into actionable recommendations that drive business outcomes
- 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
- Practical experience with Great Expectations and Evidently AI for advanced data validation
- Proficiency in cloud-based model deployment tools such as KubeFlow and BentoML
- Background in large-scale data processing and distributed computing environments
- Expertise in feature engineering and model interpretability techniques
- Familiarity with cloud-based data science platforms such as AWS SageMaker, Azure ML, or Google Cloud AI Platform
- 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 institution, such as Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate
Experience Range: With 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 Key Responsibilities:
Required Skills:
Preferred Skills:
Desired Qualifications:
Employment type
Employee
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Pune, Maharashtra, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.