Data Scientist/Senior Data Scientist
About The Position
As a Data Scientist/Senior Data Scientist , you will drive our predictive analytics innovation. Your primary goal will be to design, build, and deploy new predictive models across our entire product suite, including iWave, Ascend, and AdvancementRM. The ideal candidate is adept at building and exploiting large datasets to develop new machine learning and predictive models for SaaS products. You will have strong experience using a variety of methods (regression, random forest, XGBoost, etc.), using a variety of data tools, building, and implementing models, using/creating algorithms and creating/running simulations. You will need to be comfortable working with a wide range of stakeholders and functional teams. You will have a passion for discovering solutions hidden in large data sets and working with users to understand their needs. We’re hiring at two levels for this role. The level (Data Scientist or Senior Data Scientist) will be determined based on experience, scope and demonstrated impact.
Requirements
- Intermediate Experience: At the junior level, 3+ years of data analytics, data science, and machine learning experience.
- Senior Experience: 6+ years of data analytics, data science, machine learning experience, and preferably management experience. Experience working in Agile environments, with a strong understanding of Scrum principles.
- Technical Acumen: Mastery of Python or R to clean, structure, and model data. Preferably, experience with AWS.
- Problem Solving: Strong, detail-oriented problem solving skills and ability to work independently.
- Excellent Communicator: Strong written and verbal communication skills with a focus on internal communication across teams.
Nice To Haves
- Familiarity with Salesforce
- Familiarity with CRMs, ERPs, or fundraising technology.
Responsibilities
- Build Predictive Models: Design and implement machine learning models to predict donor behavior, giving capacity, and engagement propensity across all Kindsight products.
- Maximize the Value From Client and Third-Party Data: Evaluate the wide-range of data gathered from clients and current third-party vendors to identify new metrics and insights using existing data.
- Identify New Data Collection Opportunities: Identify additional data that could be collected within each product to develop stronger predictive models.
- Benchmarking: Design new metrics to benchmark client fundraising potential and performance.
- Partner with Head of AI: In close collaboration with our Head of AI, build agents and generative AI that leverages new predictive model results to fuel fundraising efforts.
- For Sr Level, in addition to the above; Architect & Mentor: Lead the design of scalable ML pipelines and mentor junior data scientist on best practices in statistical modeling and experimental design.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
