Senior Data Scientist

Senior Data Analyst Data Analytics:

Overview

About Business Unit:

Powerful predictors of the future - our Analytics team seamlessly blends data science and business intelligence to provide unparalleled foresight for our platform offerings. They turn insights into actionable results for our clients by collaborating with senior team members and staying ahead of market trends, powered by our data assets. By using new-age analytic tools and emerging technologies, the team cultivates a dynamic learning environment for curious minds to thrive.

Role Summary:

Senior Data Analyst is accountable for accurate, on-time delivery of multiple and concurrent statistical deliverables, builds and presents statistically sound models and profiles using current, standard programs and statistically sound techniques, translates clients needs into project plans and develops strong working relationships with key people in other departments.

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Responsibilities

Key Accountabilities:

Handle all aspects of data modeling processing – includes, but is not limited to the following:

Accuracy

• Accountable for accurate, on-time delivery of all statistical deliverables
• Ability to conduct small, medium scale projects and research through all stages: concept formulation, definition of metrics, determination of appropriate statistical methodology, research evaluation, and final research report
• Independently build and present internally statistically sound models using current, standard programs
• Apply industry techniques/ideas/trends to current systems
• Consult/explain complex statistical ideas to internal clients
• Translate clients needs into project plans
• Able to answer questions about data sets and analyses
• Able to become familiar and align with the group's policies and procedures for programming, project documentation, and system management
• Able to master the desktop and UNIX tool set (Python, SAS, SAS ODS, Excel, PowerPoint, Word) to create content for evaluating statistical analyses such as tables, reports, graphs, etc.
• Able to become proficient with the different types of quantitative modeling offerings provided by the Analytical group
• Work with internal departments to troubleshoot a variety of problems.
• Effectively explain results of troubleshooting
• Lead statistical training on standard models to other departments.
• Employ sound statistical techniques
• Able to manage to project deadlines
• Lead low - to medium-level complexity projects
• Consult with other departments on ways to improve systems
• Develop strong working relationships with key people in other departments
• May provide statistical training to stats department
• Ability to write new Python/SAS code, improve current code, and understand all code being used

On Time Delivery

• Keep Onshore updated on the status of all Models in progress
• Monitor and document progress of job through Jira system
• Responsible for managing own workload to ensure delivery on time; may require securing help from others at times
• Work with Account Specialist and Sales to troubleshoot stalled jobs due to incorrect or missing information in a timely manner
• Deals with ambiguity while maintaining composure and problems solving under tight deadlines
• Ensure successful completion and publishing of all Model requests

Effective Teams

• Builds rapport within team and across department
• Provides timely information to internal customers providing necessary information to make accurate and quality decisions
• Before leaving on PTO, arrangements are to be made within team for backup to complete all outstanding jobs; and communication made to AS regarding handoff
• Assist teammates as needed to ensure the department as a whole meets its obligation to internal and external customers

Qualifications

Interfaces / Metrics (if applicable):

• Interfaces include but are not limited to:
• Python
• SAS EG
• UNIX
• Model Performance
• Stats
• Client Services
• Data Acquisition & Data Performance
• T&D
• Meet or exceed expectations in support of department objectives including:
• Accuracy – Model results
• On Time Delivery
• Service Level Agreements are met, and workload is balanced across team
• Interpersonal Core Competencies - Effective Teams
• Accountability, Communication and Teamwork
• Protects Business Integrity
• Adheres to business best practices, demonstrates integrity and looks for new opportunities for improving quality
• Training – Knowledge and Skill Development

Minimum Qualifications:

• Bachelor's / Master's degree in a quantitative field
• 4-6 years prior experience with data analysis or modeling with large transactional databases
• Minimum 2 years experience in a statistical field
• Minimum 2 years experience conducting original research
• Experience working in Python environment is a must