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Data Scientist R
Job Location:
Monthly Salary:
Posted:
29 September 2026 (Yesterday)
Posted:
Application Deadline:
27 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Data Scientist
Job requirements
- 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
- 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
- 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
- Bachelors 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)
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:
Required Skills:
Preferred Skills:
Desired Qualifications:
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.
Required Experience:
IC
About Company
Brillio is a global leader in Enterprise Digital Transformation Solutions, providing strategic consulting services and solutions using emerging technologies.
