Senior Data Specialist
Brillio · Pune · onsite · Posted 23d ago
Undisclosed8–13 yrsfulltimeSourced from
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About this role
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.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
data qualityspssSASPythonComputer ScienceMicrosoftanalyticalMachine LearningForecastingRecruitment
About Brillio
Brillio
IT Services & Consulting
3.7k+
employees
2014
12 years old
Dallas, US state of Texas
CU
About
Brillio offers comprehensive digital transformation services, focusing on customer experience, AI, and product engineering to drive business innovation.
Industries
IT Services & ConsultingAnalytics & KPO
Employee ratings
1,318 reviews
3.4/ 5
Culture
3.2
Career growth
2.8
Work-life
3.4
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