Location: Indianapolis, IN Position Type: Remote Contract Length: 6 months + extensions Position Overview: This Data Scientist role is responsible for delivering actionable insights through advanced analytics, statistical modeling, and data science techniques, while supporting the development of scalable data solutions and tools. The position also serves as a key collaborator and mentor, partnering with stakeholders to translate business needs into data-driven strategies and fostering best practices across the organization. Duties: - Provide mentorship and guidance to junior Data Scientists and data-focused staff - Collaborate with stakeholders to understand business challenges and translate them into analytical solutions - Design, develop, and support internal web applications and interactive data tools - Analyze and assess data quality, structure, and integrity from various source systems - Partner with data engineers and BI teams to optimize data architecture, ETL processes, and reporting solutions - Develop rapid prototypes and minimally viable products to address user needs - Identify opportunities to improve processes and drive efficiencies using data science best practices - Perform data mining, statistical analysis, and modeling to generate actionable insights - Interpret and synthesize data from multiple sources using a range of analytical techniques - Maintain and manage code repositories using version control tools (e.g., GitHub) - Educate end users on interpreting and leveraging data insights effectively - Test, validate, and support enhancements to existing data solutions and systems - Provide ongoing maintenance and support for deployed data products - Document technical specifications and ensure alignment with established standards and best practices - Lead or support workshops, training sessions, and knowledge-sharing initiatives - Develop data visualizations and communicate findings to both technical and non-technical audiences - Build and deploy user-facing analytical applications using frameworks such as Shiny, Dash, Flask, or Streamlit Required Skills: - 2+ years of experience with a Bachelor’s Degree in analytics, statistics, computer science, informatics, mathematics, or a related field; or a Master’s Degree in a related field; or 4+ years of experience leveraging data to drive significant organizational impact - 2+ years of experience building user-facing applications using frameworks such as Shiny, Dash, Flask, or Streamlit, including connecting to backend data pipelines and deploying lightweight analytical tools - 2+ years of experience connecting to backend data pipelines and deploying analytical applications - 2+ years of experience using programming languages such as R, Python, and SQL to manipulate large datasets, generate insights, and develop automation solutions - 2+ years of experience applying advanced statistical techniques, including regression analysis, statistical testing, and distribution analysis - 2+ years of experience with data manipulation, including cleansing, standardizing, and transforming data - 2+ years of experience working with machine learning techniques such as clustering, decision trees, and neural networks - 2+ years of experience working with relational and dimensional databases, including their theories, principles, and best practices - Experience leading workshops or training sessions for user communities - Strong analytical, conceptual, and problem-solving skills - Experience creating and delivering data visualizations to diverse audiences - Demonstrated strategic thinking capabilities - Strong written, verbal, and presentation communication skills - Proven ability to be a resourceful, self-motivated team player - Ability to thrive in a fast-paced environment - Strong communication skills with the ability to understand and articulate complex problem nuances Preferred Skills: - Experience with geocoding and geospatial data - Experience with network diagramming and graph-based tools such as Neo4j - Experience working with containerization and orchestration tools such as Docker and Kubernetes - Additional experience with tools such as Shiny or similar advanced analytical frameworks

• Research and experiment with multifamily datasets to identify opportunities for new product features and pricing insights. • Partner with product managers and engineers to define requirements and design data-driven capabilities for ApartmentIQ's revenue management products. • Translate revenue management workflows into scalable tools and features — you should be able to sit in a pricing call and immediately understand what the revenue manager is trying to solve. • Apply LLMs and other AI techniques to accelerate research, automate workflows, and unlock new insights from structured and unstructured market data. • Design and run experiments to measure whether our data and recommendations actually drive better RM outcomes for customers. • Act as a subject matter expert on multifamily revenue management, ensuring the product reflects real-world operator needs. • Create clear documentation, dashboards, and analyses to communicate findings and product opportunities. • Stay current on multifamily industry trends, data sources, AI/ML advances, and pricing methodologies.

• A Data Scientist III in Brain Research is a senior, research-focused professional who applies advanced analytics, statistical modeling, and machine learning to support neuroscience studies and clinical discovery. • In close partnership with Principal Investigators (PIs), this role designs and executes research initiatives using multimodal neuroimaging data—including MRI, fMRI, and DTI—to examine structural and functional changes across the brain. • Key responsibilities include developing Python-based computational workflows for data preprocessing, analysis, and modeling; testing and validating hypotheses across specific brain regions; and translating complex analytical results into clear, actionable insights for research and publication. • Collaborating with cross-functional teams to design and build data-driven software systems, such as analytics platforms, data pipelines, and machine learning–enabled applications. • Advancing disease-focused research including Alzheimer’s disease, stroke, and epilepsy by uncovering patterns in brain data that inform diagnosis, disease progression, and treatment strategies. • Developing new software, data models, and proof-of-concept solutions, ensuring rigorous testing and validation to deliver reliable, production-quality outcomes while working closely with PIs throughout the research lifecycle.

• Design, build, validate, and deploy machine learning models across the full data science lifecycle, including exploratory analysis, feature engineering, model development, validation, deployment, and monitoring. • Develop advanced analytics solutions for clinical prediction, population health, operational optimization, and research enablement. • Build AI-powered applications leveraging LLM APIs, prompt engineering, and RAG pipelines to support clinical and operational workflows. • Ability to work with diverse healthcare data sources including EHRs, claims, and clinical registries. • Translate complex analytical findings into meaningful, actionable insights for clinical and operational stakeholders. • Manage documentation of best practices and scalable frameworks that can be applied across client engagements. • Mentor and guide client counterparts to build the skills needed to sustain and expand on project deliverables.