Senior Data Scientist

Requirements and Minimum Education Level

• 3+ years of experience using various programming languages (R, Python, Spark, SQL)
• Intermediate-advanced in one or more programming language (Python, PySpark, R)
• Experience with various statistical methodologies and mathematics (Generalized Additive Models (GAM), Hierarchical Linear Mixed Effects (HLM) Regression, Generalized Linear Models (GLM), Classification and Regression ensembling, Latent Analysis and Structural Equation Modeling (SEM), and unsupervised clustering segmentation models)
• Strong business acumen (understanding of how business operates, and how to harness data and analytics to meet business needs)
• Ability to develop and deploy advanced analytical models and algorithms that drive profitable growth at NUSA
• Experience visualizing/presenting data for partners using Microsoft PowerBI
• Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment
• Proven examples of developing, selling, and sharing modeling concepts across team members to drive adoption and implementation beyond personal use
• Experience in a mentorship type role, focused on driving contribution beyond own models and projects
• Excellent facilitation and presentation skills, including training delivery
• Excellent oral and written communication skills, organizational and time-management abilities
• High initiative, self-starter, and able to work with limited supervision

Responsibilities

• As a member of the EA-SRM team, the associate will serve as an advanced analytics expert in building, enhancing, and sustaining sophisticated and interconnected mathematical models and end-user applications that drive strategic decision making across the commercial organization
• Assist in the development, evaluation, and deployment of innovative data science solutions in support of our commercial decision making
• Introduce Machine Learning methodologies across a wide breadth of strategic business use cases
• Acquire deep understanding of business problems and translate them into appropriate mathematical depictions
• Act as an internal consultant by integrating with departmental customers to identify opportunities, scope and define the business problems, and assisting in the deployment of self-service tools and applications
• Interpret results, draw insightful conclusions, and present findings and recommendations to the appropriate stakeholder groups
• Engage in constructive collaboration with a broad range of team members from diverse functional backgrounds, by communicating complex ideas in palatable and understandable terms
• Research, design, estimation, and testing of a wide range of Econometric, Machine Learning, and mathematical models (Price Elasticities and Sensitivity model estimations, Revealed preference Conjoint Analysis, Classification & Regression Techniques, Principal Components Analysis, Volume Transferability model estimations, Choice Probability models, Optimization calculus, etc.)
• Adept management of the modeling and algorithm development process and cycles of design, estimation, evaluation, updating, and solution defense
• Tailor solutions, leverage code and architectural platform efficiencies, and work seamlessly across the cloud computing technical stack in both dev and prod environments
• Manage special projects, pilots, Proof of Concepts/Value (POC/POV), and ad-hoc projects, ensuring on-time delivery according to a master project plan
• Conduct proper stakeholder management to ensure all parties are aligned and updated throughout the project life cycle
• Act as a consultant in the capacity of publishing, educating, and securing acceptance of complex mathematical concepts and models from various stakeholders
• Develop professional presentations and project status reporting appropriate for their intended audience

Qualifications

• Undergraduate Degree in Computer Science, Engineering, Mathematics, Statistics, Business, or a similar field; Master's degree preferred
• 3+ years of experience using various programming languages (R, Python, Spark, SQL)
• Intermediate-advanced in one or more programming language (Python, PySpark, R)
• Experience with machine learning methodologies and algorithms (Regression, Bayesian statistics, Clustering, Classification, Probability Networks, etc.) in a Consumer Packaged Goods industry or context preferred
• Experience with various statistical methodologies and mathematics (Generalized Additive Models (GAM), Hierarchical Linear Mixed Effects (HLM) Regression, Generalized Linear Models (GLM), Classification and Regression ensembling, Latent Analysis and Structural Equation Modeling (SEM), and unsupervised clustering segmentation models)
• Strong business acumen (understanding of how business operates, and how to harness data and analytics to meet business needs)
• Ability to develop and deploy advanced analytical models and algorithms that drive profitable growth at NUSA
• Experience modeling and productionalizing models in notebook environments (Microsoft Azure preferred)
• Experience visualizing/presenting data for partners using Microsoft PowerBI
• Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment
• Proven examples of developing, selling, and sharing modeling concepts across team members to drive adoption and implementation beyond personal use
• Experience in a mentorship type role, focused on driving contribution beyond own models and projects
• Excellent facilitation and presentation skills, including training delivery
• Excellent oral and written communication skills, organizational and time-management abilities
• High initiative, self-starter, and able to work with limited supervision