SSB Consulting Group LLC
Kindsight builds technology that helps fundraisers make a difference. For decades, Kindsight has supported the education, healthcare, and nonprofit sectors with fundraising tools and the largest charitable giving database on the market. And as the giving sector evolves, so does Kindsight. As the leader in fundraising intelligence, Kindsight leverages real-time data and AI to help thousands of organizations around the world identify, manage, and engage with donors-at any scale. With purpose-built CRMs that corral all of that donor information and campaign tracking into one place, donor prospect research tools that offer proactive insights and real-time donor intel, and generative AI that creates personalized, meaningful content drafts at scale, Kindsight's product suite is truly changing the game for donor fundraising.
POSITION DESCRIPTION SUMMARY
Affinaquest seeks a data scientist to join our Product Engineering team. In this role, you'll work on our Client Data Platform (CDP) and analytics platform, applying machine learning and software engineering practices to empower institutions in fundraising and athletic operations. Affinaquest analyzes client data to uncover actionable insights that drive our clients' missions forward.
You'll work with Azure Machine Learning, Snowflake, dbt, Python, and Airflow to enhance our data stack and evolve our machine learning outputs from our current supervised learning models and predictive analytics to emerging unsupervised and prescriptive analytics.
Affinaquest is looking for someone with a strong software engineering background, fluent in modern tooling and open frameworks, who will collaborate with Product Engineering peers and client innovation partners to shape our platform's evolution and deliver value to clients. A passion for technical curiosity for uncovering hidden metrics, fresh statistical insights, and untapped value within data.
In this role, you'll have a heavy hand in the architecture, processes, and tools behind machine learning and data analytics initiatives, delivering predictive models and backend data discovery processes that pave the way for future modeling.
Working closely with Product Leaders and Data Engineers, you'll ensure your models offer accurate, actionable insights, while actively participating in Scrum ceremonies to refine user stories and acceptance criteria.
KEY RELATIONSHIPS
Reports to:
Sr Manager of Product Engineering
Other key relationships:
Product Leaders and the Product Delivery Team
Requirements
MANDATORY QUALIFICATIONS TO APPLY
BS degree in data science, computer science, engineering, or equivalent experience 5+ years' experience with software development best practices including unit testing and code review processes. 3+ years' experience in data manipulation within SQL. 2+ years' experience in model selection, validation, and model performance metrics. Pragmatic approach to problem solving which prioritizes delivering working solutions to real problems. Strong understanding of the full lifecycle of model development. Demonstrated history of solving impactful business problems using statistics, machine learning, and data analysis. US-Based PRIMARY RESPONSIBILITIES AND ACTIVITIES INCLUDE
Utilize Azure Machine Learning, including Automated ML, for model prototyping. Utilize Airflow for workflow automation and orchestration of data pipelines. Perform data warehousing functions within Snowflake and transform data using dbt. Serve as the subject matter expert in Python and the evolving data science stack-from core libraries like Pandas, NumPy, and Scikit-learn to advanced frameworks like XGBoost and emerging alternatives to drive continuous model innovation and optimization. Implement MLOps practices to streamline the deployment and management of machine learning models. Develop and evolve machine learning models, initially focusing on supervised learning and progressively incorporating unsupervised and prescriptive analysis techniques. Collaborate with internal stakeholders and clients to understand business requirements and deliver data-driven solutions. Communicate results and insights to stakeholders through clear, end-user-oriented reports and presentations. Drive innovation and contribute to our client's success with impactful data science solutions. IDEAL ATTRIBUTES AND PROVEN CAPIBILITIES
Azure Machine Learning experience Snowflake, dbt, and/or Airflow experience Experience with delivering predictive models and scores for advancement/fundraising and/or ticketing data Experience in fundraising, donor management, or advancement analytics. Technical curiosity for uncovering hidden metrics and statistical insights. You enjoy understanding the data and finding meaningful, related, untapped value from the data. Experience with time series forecasting Causal modeling over observational data Tableau dashboards and KPI tracking POSITION LOCATION
Corporate Headquarters
( ASU SkySong, Scottsdale, AZ ) - Hybrid Office Policy: Employees near an office must be there on Tuesday, Wednesday, and Thursday to foster community and engagement.
TRAVEL REQUIRED
None
Affinaquest is an equal-opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
Salary Description
$150,000- $160,000
POSITION DESCRIPTION SUMMARY
Affinaquest seeks a data scientist to join our Product Engineering team. In this role, you'll work on our Client Data Platform (CDP) and analytics platform, applying machine learning and software engineering practices to empower institutions in fundraising and athletic operations. Affinaquest analyzes client data to uncover actionable insights that drive our clients' missions forward.
You'll work with Azure Machine Learning, Snowflake, dbt, Python, and Airflow to enhance our data stack and evolve our machine learning outputs from our current supervised learning models and predictive analytics to emerging unsupervised and prescriptive analytics.
Affinaquest is looking for someone with a strong software engineering background, fluent in modern tooling and open frameworks, who will collaborate with Product Engineering peers and client innovation partners to shape our platform's evolution and deliver value to clients. A passion for technical curiosity for uncovering hidden metrics, fresh statistical insights, and untapped value within data.
In this role, you'll have a heavy hand in the architecture, processes, and tools behind machine learning and data analytics initiatives, delivering predictive models and backend data discovery processes that pave the way for future modeling.
Working closely with Product Leaders and Data Engineers, you'll ensure your models offer accurate, actionable insights, while actively participating in Scrum ceremonies to refine user stories and acceptance criteria.
KEY RELATIONSHIPS
Reports to:
Sr Manager of Product Engineering
Other key relationships:
Product Leaders and the Product Delivery Team
Requirements
MANDATORY QUALIFICATIONS TO APPLY
BS degree in data science, computer science, engineering, or equivalent experience 5+ years' experience with software development best practices including unit testing and code review processes. 3+ years' experience in data manipulation within SQL. 2+ years' experience in model selection, validation, and model performance metrics. Pragmatic approach to problem solving which prioritizes delivering working solutions to real problems. Strong understanding of the full lifecycle of model development. Demonstrated history of solving impactful business problems using statistics, machine learning, and data analysis. US-Based PRIMARY RESPONSIBILITIES AND ACTIVITIES INCLUDE
Utilize Azure Machine Learning, including Automated ML, for model prototyping. Utilize Airflow for workflow automation and orchestration of data pipelines. Perform data warehousing functions within Snowflake and transform data using dbt. Serve as the subject matter expert in Python and the evolving data science stack-from core libraries like Pandas, NumPy, and Scikit-learn to advanced frameworks like XGBoost and emerging alternatives to drive continuous model innovation and optimization. Implement MLOps practices to streamline the deployment and management of machine learning models. Develop and evolve machine learning models, initially focusing on supervised learning and progressively incorporating unsupervised and prescriptive analysis techniques. Collaborate with internal stakeholders and clients to understand business requirements and deliver data-driven solutions. Communicate results and insights to stakeholders through clear, end-user-oriented reports and presentations. Drive innovation and contribute to our client's success with impactful data science solutions. IDEAL ATTRIBUTES AND PROVEN CAPIBILITIES
Azure Machine Learning experience Snowflake, dbt, and/or Airflow experience Experience with delivering predictive models and scores for advancement/fundraising and/or ticketing data Experience in fundraising, donor management, or advancement analytics. Technical curiosity for uncovering hidden metrics and statistical insights. You enjoy understanding the data and finding meaningful, related, untapped value from the data. Experience with time series forecasting Causal modeling over observational data Tableau dashboards and KPI tracking POSITION LOCATION
Corporate Headquarters
( ASU SkySong, Scottsdale, AZ ) - Hybrid Office Policy: Employees near an office must be there on Tuesday, Wednesday, and Thursday to foster community and engagement.
TRAVEL REQUIRED
None
Affinaquest is an equal-opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
Salary Description
$150,000- $160,000