Sr. Data Analyst

Come and See•Colorado Springs, CO

1d•Onsite

About The Position

The Sr. Data Analyst / Data Scientist I serves as a bridge between advanced analytics and actionable business intelligence at Come and See Foundation. This role applies sophisticated analytical methods, machine learning, and data storytelling to uncover insights that drive ministry impact across a global, multi-platform audience. Working at the intersection of donor analytics, digital product performance, and audience engagement, the ideal candidate is deeply technical, highly curious, and passionate about using data to advance mission-driven outcomes. Proficiency in Snowflake and Tableau is essential, and experience with donor, product, or nonprofit data ecosystems is a strong plus.

Requirements

Expert-level proficiency in Tableau for dashboard development and data visualization
Advanced SQL skills, including complex queries and transformations within Snowflake
Proficiency in Python, JMP, or R for data analysis, statistical modeling, and machine learning
Experience with Google Analytics for web and audience behavioral analysis
Working knowledge of CRM platforms, preferably Virtuous or HubSpot
Familiarity with machine learning libraries (scikit-learn, XGBoost, LightGBM, or similar)
Proficiency in Excel for ad hoc analysis and stakeholder reporting
Experience with Git/GitHub for version control
Analytical Thinking: Methodical, diligent, and able to approach complex problems with an analytical mindset
Storytelling: Translates data into compelling, decision-driving narratives for diverse audiences
Communication: Clearly presents complex findings both verbally and in written form; able to influence cross-functional teams and leadership
Collaboration: Builds productive relationships with cross-functional partners across the organization
Integrity: Handles data and findings with transparency, honesty, and ethical responsibility
Adaptability: Adjusts priorities effectively in a fast-paced, mission-driven environment
High Standards: Holds self and work to a consistently high bar for quality and accuracy
Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
5+ years of experience in data analysis, business intelligence, data science, or product analytics roles
Demonstrated experience with Snowflake and Tableau in a professional setting

Nice To Haves

Familiarity with RudderStack or other customer data platforms (CDPs)
Experience with A/B testing and experimentation techniques
Understanding of ETL/ELT processes and data pipeline concepts
Experience working with mobile or app product analytics
Confidence in fundraising and donor churn analytics
Knowledge of data privacy regulations such as GDPR and CCPA
Experience working with donor, product, CRM, or nonprofit data a strong plus
Passion for faith-driven initiatives and an understanding of the unique challenges and opportunities in content and ministry work preferred
Portfolio or examples of dashboards, models, or analytical projects preferred

Responsibilities

Perform complex statistical analyses and predictive modeling using Python, R, JMP, or SQL to support organizational decision-making
Design and develop interactive Tableau dashboards and reports for senior leadership and cross-functional stakeholders
Clean, preprocess, and validate large datasets within Snowflake to ensure accuracy and analytical integrity
Apply data mining and segmentation techniques to identify patterns in donor behavior, giving trends, and ministry and audience engagement
Develop and maintain predictive models (including XGBoost, LightGBM, and scikit-learn approaches) to forecast ministry trends and program outcomes
Leverage Excel for ad hoc analysis, data validation, and stakeholder-facing reporting
Define, build, and maintain a comprehensive reporting framework covering product performance, audience engagement, and donor insights
Own and monitor key performance indicators (KPIs) that evaluate the effectiveness of digital products, fundraising initiatives, and ministry programming
Build and maintain BI dashboards and executive-level reports that clearly communicate data insights to both technical and non-technical audiences
Collaborate with program, fundraising, product, and ministry teams to understand business requirements and translate them into analytical solutions
Analyze donor data from Virtuous and FundraiseUp to understand giving behavior, retention patterns, and audience segmentation
Leverage Google Analytics to analyze web and app audience engagement data, connecting digital behavior - including international and mobile audiences - to ministry and fundraising outcomes
Identify trends and actionable opportunities through in-depth analysis of audience, product, and giving data
Serve as a data evangelist, helping colleagues understand and confidently use data in their work
Apply machine learning algorithms to build, train, and optimize models for organizational use cases such as donor scoring and audience segmentation
Support and extend the Customer 360 intelligence platform, including predictive scoring models and AI-powered analytics
Explore NLP and other AI techniques as applicable to ministry communications, survey feedback, and content analysis
Support A/B testing and experimentation frameworks to evaluate product features, content strategies, and fundraising approaches
Document methodology, model assumptions, and results to ensure reproducibility and transparency
Collaborate with the Data Engineering team to ensure Snowflake pipelines and data models meet analytical requirements
Write and optimize complex SQL within Snowflake, leveraging native transformation capabilities to prepare and structure data for analysis
Monitor data quality and apply rigorous validation to ensure the accuracy and reliability of reporting outputs
Support integration and analysis of data from RudderStack event streams, HubSpot, Virtuous, and FundraiseUp
Ensure data collection and usage comply with global privacy standards including GDPR and CCPA
Ensure all data practices comply with applicable privacy regulations (GDPR, CCPA) and internal governance policies
Apply access control best practices and handle sensitive donor and constituent data with discretion and care
Actively identify and mitigate biases in data collection, analysis, and modeling processes
Champion transparency and ethical AI practices across the data science function
Partner with stakeholders across programs, communications, fundraising, product, and executive leadership to deliver insights that influence strategic decisions
Present data-driven insights and analytical findings to senior leadership and cross-functional teams in a clear, compelling, and action-oriented manner
Translate complex data findings into narratives and visualizations accessible to both technical and non-technical audiences
Use Git/GitHub for version control, code collaboration, and documentation of analytical work
Document processes, data definitions, and analytical frameworks for team knowledge sharing