Title: Senior Data Scientist/Data Analyst Location: Schenectady, New York Job Description: Jahnel Group’s mission is to provide the absolute best environment for software creators to pursue their passion by connecting them with great clients doing meaningful work. We get to build some of the most complex and compelling applications for our clients located across the country. We’re a fast-growing INC 5000 recognized company, yet we still work as a very close-knit team (100+ employees). We’re growing like crazy, and if you’re looking for the next place to call home, hit us up for a beer or coffee. Who We're Looking For We’re on the hunt for a Senior Data Scientist/Data Analyst who thrives in building scalable financial systems and integrations. Someone who takes ownership, translates business needs into reliable solutions, and ensures data integrity across systems. If you’re strong in Python, SQL, NetSuite, Celigo, and APIs, this could be your next move. Primary Responsibilities - Act as the primary embedded developer supporting finance, operations, and asset management teams - Build and maintain Python-based solutions for financial systems and workflows - Own end-to-end delivery of business-critical tools, from requirements through deployment - Translate stakeholder needs into scalable technical solutions with a consultative approach - Manage data pipelines and ensure data integrity, accuracy, and reliability - Support financial visibility and cash management initiatives through data analysis and system improvements - Collaborate cross-functionally and drive progress across multiple in-flight projects Some Must-Haves: - 5+ years of experience in Data Scientist / Data Analyst or related roles. - Expert-level Python, including complex domain modeling, refactoring, and test development - Strong SQL experience for data querying and transformation - Hands-on experience with Celigo for building and troubleshooting integrations - Deep understanding of NetSuite data models, objects, and API/SuiteScript ecosystem - Working knowledge of Salesforce data models and integration patterns - Experience designing and consuming REST APIs - Familiarity with cloud services (e.g., AWS S3 or Azure Key Vault) - Proven experience building and maintaining data pipelines (ETL/ELT) Where We're Looking For It: - Schenectady, New York - Open to 100% Fully Remote Other Information The work hours will be approximately 9:00 am to 5:00 pm EST, depending on workload, with the occasional late night when a tight deadline calls for it. We work for security-conscious clients, thus background checks will be required. Position available immediately.

• Execute and manage all in house clinical data management activities for assigned oncology trials in accordance with ICH/GCP, regulatory requirements, and internal SOPs • Support and contribute to the oversight of CROs and data management vendors, including review of deliverables, metrics, timelines, and issue escalation • Perform and/or oversee database build, edit check specification review, UAT planning and execution, database modifications, and database lock activities • Conduct ongoing data review, cleaning, query management, and quality control to ensure data accuracy, consistency, and completeness • Develop, review, and maintain Data Management deliverables, including: Data Management Plans (DMPs), CRF Completion Guidelines, Data Validation Specifications, and Data Transfer Specifications • Monitor study status metrics and provide regular data management status updates to study teams and functional leadership • Collaborate cross functionally with Clinical Operations, Medical Writing, Medical Monitoring, Biostatistics, and Safety to support data reconciliation, analysis readiness, and submission activities • Identify operational risks, trends, and data quality issues using metrics, audits, and study insights, and partner with teams to implement corrective actions • Support inspection readiness activities, audits, and regulatory inquiries related to clinical data management

• Build, iterate, and launch models to a production environment focused on predicting outcomes in sports. • Train machine learning models and build statistical modeling frameworks using custom methods, or using xgboost, sklearn, pytorch, etc. • Manage SQL queries to ensure data pipelines are efficient, accurate, and up to date. • Rigorously backtest models to ensure highly accurate predictions.

• Design, develop, and maintain scalable data pipelines using PySpark to efficiently process large volumes of data. • Develop, test, and optimize Machine Learning models for predictive analytics, including regression, classification, and clustering techniques. • Manage and deploy Machine Learning environments and workflows using AWS SageMaker, while leveraging Athena for data querying and analysis. • Integrate Machine Learning models into production pipelines, ensuring proper monitoring, maintenance, and continuous improvement through MLOps best practices. • Collaborate closely with cross-functional teams to understand business challenges and translate them into data-driven solutions. • Conduct advanced data analysis using Python and SQL to deliver actionable insights. • Work collaboratively with multidisciplinary teams using Git/GitHub and agile development methodologies.