- Leverage data science to understand and design analytical solutions to business problems
- Understand requirements stakeholders' requirements
- Propose and execute solutions, and present deliverables to stakeholders
- Manage and optimize deliverables
- Mentor and train new team members
- Develop POCs to enhance the team's capability
Skill Set
- Strong understanding of mathematical, statistical, and theoretical foundations of statistics and machine learning (ML), along with parametric and non-parametric models
- Robust knowledge of advanced data mining, curating, processing, and transforming techniques
- Knowledge of statistical techniques and ML methods for predictive modeling / classification of problems around clients, distribution, sales, client profiles, and segmentation
- Ability to provide relevant and actionable recommendations / insights for businesses
- Understanding of ML lifecycle, including feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop
- Expertise in SAS Visual Analytics, Tableau, and Python
- Expertise in Python / R / SAS
- Experience with cloud computing infrastructure, such as AWS / Azure / GCP
- Ability to develop, test, and deploy models on cloud / web
Keyskills: machine learning python data analysis sql analytics sas visual analytics data mining data science cloud computing client profiles statements of work sow
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