Data Science Lead

Data Science Lead (Classic ML)

10+ years required

Remote role,

W2(Independent Contractors)

Experience Range: 10+ years of experience in advanced data science roles, including leadership of machine learning and statistical modeling projects

Key Responsibilities:

1. Lead the design, development, and deployment of Next Best Offer models and advanced data science solutions to drive business growth

2. Apply statistical techniques including hypothesis testing, t-tests, z-tests, regression (linear and logistic), and forecasting to generate actionable insights

3. Oversee end-to-end machine learning workflows using Python, PySpark, and R, ensuring robust model development, validation, and continuous improvement

4. Leverage probabilistic graph models and advanced classification algorithms such as decision trees and support vector machines to address complex business challenges

5. Implement and optimize scalable machine learning pipelines using KubeFlow and BentoML for production environments

6. Conduct statistical analysis and computing utilizing SAS, SPSS, and R Studio to support data-driven decision-making

7. Evaluate, monitor, and refine model performance to ensure accuracy, reliability, and business impact

8. Collaborate with cross-functional teams to translate business requirements into effective data-driven strategies and measurable outcomes

Required Skills:

1. Python

2. PySpark

3. SAS

4. SPSS

5. R

6. R Studio

7. Probabilistic graph models

8. Regression methods (linear and logistic)

9. Forecasting methods (exponential smoothing, ARIMA, ARIMAX)

10. Decision trees

11. Support Vector Machines (SVM)

12. TensorFlow

13. PyTorch

14. Scikit-learn

15. CNTK

16. Keras

17. MXNet

18. KubeFlow

19. BentoML

Preferred Skills:

1. Great Expectation

2. Evidently AI

3. Cloud-based machine learning deployment

4. Advanced ensemble methods

5. Boosting algorithms

6. A/B testing

7. Experimental design

8. Recommendation systems

9. Personalization algorithms

Desired Qualifications:

1. Bachelors degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline

2. Certification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCamp

3. Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst