Senior Data Scientist - R01566194

1. Design and implement advanced statistical models and machine learning algorithms to solve complex business challenges
2. Develop, validate, and deploy predictive models using Python, R, or PySpark, ensuring high accuracy and scalability
3. Conduct rigorous hypothesis testing, including T-Test and Z-Test, to drive data-driven decision making and uncover actionable insights
4. Apply regression techniques such as linear and logistic regression to analyze trends, forecast outcomes, and optimize business processes
5. Utilize time series forecasting methods, including ARIMA, ARIMAX, and exponential smoothing, to deliver accurate demand and trend predictions
6. Leverage classification methods such as decision trees and support vector machines to segment data and enhance model performance
7. Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings effectively
8. Ensure model reliability and compliance by implementing robust validation frameworks and tools, including Great Expectations and Evidently AI

Do you have experience in Time series models?, Do you have a Master's degree?, * Experience Range: 5 - 8 years of experience in advanced data science roles, 1. Advanced proficiency in Python and PySpark for data analysis and modeling

2. Expertise in statistical analysis and computing, including hypothesis testing, T-Test, and Z-Test

3. Hands-on experience with regression techniques (linear and logistic regression)

4. Practical knowledge of probabilistic graph models

5. Experience with forecasting methods such as exponential smoothing, ARIMA, and ARIMAX

6. Proficiency in classification algorithms, including decision trees and support vector machines (SVM)

7. Strong command of ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet

8. Skilled in using statistical tools like SAS and SPSS

9. Familiarity with R and R Studio for statistical modeling

10. Experience with distance metrics (Hamming, Euclidean, Manhattan Distance) Preferred Skills:

11. Experience implementing data validation frameworks such as Great Expectations and Evidently AI

12. Knowledge of model deployment tools like KubeFlow and BentoML

13. Background in handling large-scale data processing and distributed computing environments

14. Expertise in feature engineering and dimensionality reduction techniques

15. Familiarity with automated machine learning (AutoML) pipelines Desired Qualifications:

16. Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field

17. Relevant certifications in data science, machine learning, or statistical analysis are a plus

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.