Principal Data Analyst, EIM Analytics

Ascensus•Needham, MA

About The Position

As a Principal Data Analyst at Ascensus, you will collaboratively develop, communicate, and execute the data analytics and data management roadmap and vision. You will lead and perform analytics and data management work, including supporting data scientist studies through data mining, managing and expanding analytics data sources, conducting analyses that drive business value, and communicating insights through reports and visualizations. You will coordinate with the EIM team to transition prioritized data and reports to the EIM platform and identify, justify, and implement new tools and technologies as needed. You may also support overflow needs of the Analytics & Insight team. The role includes strategy and planning, project and workload management, data analysis, business intelligence reporting, and data management. You will maintain the roadmap, align priorities with business strategy, identify technology needs, execute projects, manage milestones and risks, and support team development. You will validate data sources, assess and improve data quality, prepare and analyze data, monitor models and scheduled jobs, and contribute to data governance. You will also document analytics data sources and ETL processes and design, code, tune, and modify ETL solutions in alignment with Ascensus standards and design guidelines. The position is responsible for protecting confidential Ascensus data from unauthorized access, improper transmission, and unapproved disclosure. The role may include small-team supervision, including mentoring and developing staff, setting goals, providing feedback, supporting education, managing deliverables, and handling leadership and administrative responsibilities such as performance reviews and time-off administration. Actions should reflect Ascensus’s I-Client service philosophy and its Core Values of People Matter, Quality First, and Integrity Always.

Requirements

Postgraduate degree in data, mathematics, or a related field.
At least 10 years of data-related experience with a demonstrated ability to derive business value through analysis.
Advanced analytics and data-mining ability, including selecting appropriate analytical techniques and translating findings into actionable business insights and recommendations.
Knowledge of mathematical principles and methods and the ability to apply experience, research, and expertise to achieve goals.
Understanding of data warehousing concepts, including data marts and data definition practices that support data quality and reuse.
Ability to write complex SQL statements to store, retrieve, manipulate, integrate, validate, and summarize data.
Strong verbal and written communication skills, including the ability to explain complex concepts to nontechnical audiences.
Strong interpersonal and collaboration skills and ability to work with internal business partners across the organization.
Experience building business relationships and ability to learn Ascensus products, services, clients, and business considerations and obtain insight through discussions with subject matter experts.
Ability to manage time and lead others in prioritizing work, meeting deadlines, delivering valuable results, managing tasks, resolving priority conflicts, and establishing shared expectations with clients.
Initiative and strong work ethic, including driving efforts to completion, managing personal goals, and proactively seeking opportunities for successful outcomes.
Excellent analytical skills.
Experience with relational databases such as Sybase ASE, SQL Server, Oracle, or MySQL.
Proven data-structure experience or education, including organization, management, and storage formats.
Experience building business intelligence reports and dashboards.
Broad experience with database and statistical technologies and ability to learn new technologies and advise on suitable solutions.

Nice To Haves

Formal or informal leadership experience.
Retirement or Government Savings domain knowledge.
Working knowledge of Ascensus data sources, including their purpose, structure, definitions, and how data is populated.
At least 2 years of Microsoft DBA skills, including SSIS, SQL, and BCP, with experience using recent versions of Microsoft SSIS.
At least 2 years of relevant experience in an ETL or data analyst role, including data mining and/or ETL development.

Responsibilities

Develop, communicate, and maintain the data management and data analytics roadmap and vision.
Collaborate with business leaders and the analytics team to align priorities with team needs and business strategy.
Identify technology gaps and needs, investigate options, and present recommended solutions.
Coordinate with EIM to transition data and reporting priorities to the EIM platform for enterprise delivery through line-of-business reporting and dashboard solutions.
Execute the data management and analytics roadmap and support workload delegation and ad hoc requests.
Maintain milestone-level project plans, anticipate resource needs, mitigate risks, and deliver work on time.
Mentor and train analytics team members as requested.
Validate that data sources meet the requirements of analytics efforts and outcomes.
Analyze data quality and identify improvements and solutions for data gaps.
Develop a working understanding of Ascensus data sources, including their purpose, structure, definitions, and population methods.
Perform data preparation in the CRISP-DM methodology as a leader or project team member.
Perform data segmentation, review, and reporting across expansive data sources.
Monitor and chart data and models for scheduled ongoing jobs.
Follow data governance practices and recommend improvements.
Communicate analytics findings and machine learning updates and results to the business using BI and other available tools.
Develop knowledge of Ascensus business intelligence resources and guide users to them.
Create and maintain documentation for current and future analytics data sources.
Design and document ETL processes for analytics data sources.
Design, code, tune, and modify ETL solutions for analytics data sources.
Apply Ascensus ETL standards and best practices in collaboration with data scientists, DBA leadership, and the EIM team.
Protect and properly handle confidential Ascensus data to prevent unauthorized access, improper transmission, or unapproved disclosure.
If supervising a small team, support the design, mentorship, and progress of the analytics practice and ensure team members have appropriate tools and technologies.
Develop staff skills, encourage strong performance, coach improvement areas, and support employee development goals.
Foster creativity and intellectual curiosity within the team and in collaboration with others.
Manage staff needs, education, goals, objectives, and performance, and perform leadership and administrative tasks such as performance reviews and time-off administration.
Demonstrate Ascensus’s I-Client service philosophy and Core Values in day-to-day work.