The Role
Develops advanced statistical and machine learning models for forecasting, classification, prediction, and probabilistic analysis. Uses Python, PySpark, R, SAS, SPSS, and multiple ML frameworks to build, validate, deploy, and manage scalable models. Applies time-series techniques, data quality validation, feature engineering, and model interpretability. Communicates complex findings to stakeholders and translates analytical results into actionable business recommendations.
Summary Generated by Built In
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:
Skills Required
- At least 4 years of hands-on experience in advanced data science, statistical analysis, and machine learning
- Advanced hypothesis testing, including T-Test and Z-Test
- Expert regression analysis using linear and logistic regression
- Proficiency in Python and PySpark
- Extensive statistical analysis experience using SAS and SPSS
- Hands-on expertise with probabilistic graph models
- Mastery of time-series forecasting, including exponential smoothing, ARIMA, and ARIMAX
- Experience with classification algorithms, including decision trees and support vector machines
- Familiarity with TensorFlow, PyTorch, scikit-learn, CNTK, Keras, and MXNet
- Knowledge of Hamming, Euclidean, and Manhattan distance metrics
- Skilled in R and RStudio for statistical analysis and visualization
- Experience with Great Expectations and Evidently AI
- Proficiency with KubeFlow and BentoML for model deployment
- Background in large-scale data processing and distributed computing
- Expertise in feature engineering and model interpretability
- Familiarity with AWS SageMaker, Azure ML, or Google Cloud AI Platform
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related discipline
- Data Science or Machine Learning certification from a recognized institution
Brillio Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Brillio and has not been reviewed or approved by Brillio.
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Healthcare Strength — Healthcare is considered comprehensive, including medical coverage for employees and dependents alongside life, disability, and accidental death protections. Feedback suggests these protections are a core strength of the package.
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Leave & Time Off Breadth — Time-off options include paid leave and parental leave, with flexible or ‘flexible PTO’ approaches cited in some contexts. Feedback suggests this breadth helps support work-life balance when team norms permit usage.
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Wellbeing & Lifestyle Benefits — Wellbeing offerings span counseling, financial-management sessions, fitness programs, and travel insurance, plus region-specific extras like discounted IT hardware and work-from-home essentials. Feedback suggests these add-ons enhance perceived value beyond core insurance.
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The Company
What We Do
Brillio is the leader in global digital business transformation, applying technology with a human touch. We help businesses define internal and external transformation objectives, and translate those objectives into actionable market strategies using proprietary technologies. With 2600+ experts and 13 offices worldwide, Brillio is the ideal partner for enterprises that want to quickly increase their core business productivity, and achieve a competitive edge, with the latest digital solutions.
