Data Management and Governance Lead

Role Overview

• Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization.
• Formulate hypotheses and test them using math, statistics, visualization and predictive modeling.
• Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business.
• Work with stakeholders to determine how to use business data for business solutions/insights.
• Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications.
• Coordinate with other technical/functional teams to implement models and monitor results.
• Select, acquire and integrate data for analysis.
• Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data.
• Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy.
• Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire.
• Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making.
• Contribute to exploration and experimentation in data visualization and manage reviews of the benefits and value of analytics techniques and tools and recommend improvements.

Requirements

• Strong quantitative skillset with experience in statistics and linear algebra.
• Knowledge/experience with statistical programming languages including R, Python, SQL, etc.
• Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc.
• Knowledge and experience in advanced statistical techniques and concepts including regression, distribution properties, statistical testing, etc.
• Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc.
• Ability to use data visualization tools to showcase data for stakeholders.
• Good communication skills to promote cross-team collaboration.
• Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc.

Tech Stack

• Java
• JavaScript
• Python
• SQL

Benefits

• Relocation Support Available? No