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Job Description: This job is responsible for analyzing and interpreting large datasets to uncover potential revenue generation opportunities and develop effective risk management strategies. Key responsibilities include collaborating with key stakeholders to comprehend business problems, utilizing data gathering and analysis techniques to devise solutions, and presenting recommendations based on the findings. Job expectations include demonstrating flexibility, resilience, accountability, a disciplined approach, and a commitment to fostering responsible growth for the enterprise.
Responsibilities:
Performs business analytics, which includes data analysis, trend identification, and pattern recognition, using advanced techniques (e.g., machine learning, text mining, statistical analysis, etc.) to support decision-making and drive data-driven insights
Applies agile practices for project management, solution development, deployment, and maintenance
Creates and maintains technical documentation, capturing the business requirements and specifications related to the developed analytical solution and its implementation in production
Manages multiple priorities and maintains quality and timeliness of work deliverables such as quantitative models, data science products, data analysis reports, or data visualizations, while exhibiting the ability to work independently and in a team environment
Delivers engaging presentations and engages in both in-person and virtual conversations that effectively communicate technical concepts and analysis results to a diverse set of internal stakeholders, and develops professional relationships to foster collaboration on work deliverables
Mitigates risk by identifying potential issues and developing controls
Researches the latest advances in the fields of data science and artificial intelligence to support business analytics
Skills:
Adaptability
Attention to Detail
Business Analytics
Technical Documentation
Written Communications
Agile Practices
Application Development
Collaboration
Data Visualization
DevOps Practices
Artificial Intelligence/Machine Learning
Networking
Policies, Procedures, and Guidelines Management
Presentation Skills
Risk Management
Position Summary:
We are actively searching for a qualified Entry level Data Scientist with a background in technology development and engineering. The role focuses on data analytics and point insights to understand the relationships within our data sets and thus to provide risk insights and predictors and to analyze failure patterns, relationships, contradictions, and evidence of material change in our critical application and services. The role is a direct report to the head of Global Business Resiliency and Continuity. Unlike reporting and metrics, this is a content role to help us deepen our insights through targeted analytics. The role also has the potential to develop Point “smart” automation of tasks and prototypes pending full application features, statistical monte carlo models, and to provide data interactive models to support rich simulation exercises.
Required Qualifications:
Content Leader with Tech Background
Experience with R and Python, and ideally Alteryx and Tableau
Knowledge of analytic techniques and statistical modelling including optimization, correlation, and probability
Ability to build predictive models and inferential models.
Ability to use data with referential integrity.
Ability to create clean code and model explainability.
Highly organized, ability to simultaneously prioritize tasks and handle numerous time-sensitive issues.
Identifies linkages and thinks "enterprise" across business lines and geographies.
Embraces and drives changes.
Proactively takes a leadership role to ensure team success.
Drives positive energy across the team.
Analytical/strong attention to detail
Proficient Excel, PowerPoint, SharePoint, & Outlook skills
Strong written & verbal communication skills
Strong meeting facilitation skills
Desired Qualifications:
3+ years of tech architecture and / or analytic experience
Experience in failure analysis and contingency planning
Experience in Computer Science, Software Engineering, or Data Science / Business Analytics
