Brillio
Website:
brillio.com
Company:
https://www.linkedin.com/company/brillio
Seniority: Not Applicable
Industries: Artificial Intelligence
Job details:
Data Scientist
Job requirements
Experience Range: With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects
Key Responsibilities:
- Develop and implement Next Best Offer models and advanced data science solutions to drive business objectives and enhance customer engagement
- Apply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-making
- Build, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliability
- Leverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challenges
- Optimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiency
- Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategies
- Monitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectiveness
- Collaborate with cross-functional teams to translate business requirements into impactful data science solutions
Required Skills:
- Python
- PySpark
- SAS
- SPSS
- R
- Probabilistic graph models
- Regression methods (linear and logistic)
- Forecasting methods (exponential smoothing, ARIMA, ARIMAX)
- TensorFlow
- PyTorch
- Scikit-learn
- CNTK
- Keras
- MXNet
- Decision trees
- Support Vector Machines (SVM)
- Distance metrics (Hamming, Euclidean, Manhattan)
- KubeFlow
- BentoML
Preferred Skills:
- Experience with Great Expectations and Evidently AI for model validation and monitoring
- Expertise in deploying machine learning models in cloud-based environments
- Knowledge of advanced ensemble methods and boosting algorithms
- Familiarity with A/B testing and experimental design
- Background in recommendation systems and personalization algorithms
Desired Qualifications:
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline relevant to data science
- Certification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCamp
- Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst
Click on Apply to know more.
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