<p>We are seeking a Data Scientist to support and enhance production analytics and machine learning solutions. This role focuses on improving model performance, scalability, and reliability while partnering with cross-functional teams to deliver impactful data-driven outcomes.</p><p><br></p><p><strong>Responsibilities</strong></p><ul><li>Develop, evaluate, and deploy machine learning and analytics solutions in production environments.</li><li>Analyze existing models and data workflows; identify opportunities for improvement and modernization.</li><li>Collaborate with product, engineering, and business teams to deliver scalable solutions.</li><li>Establish performance monitoring, testing, and iteration processes for continuous improvement.</li><li>Contribute to data pipeline development and ensure high-quality, reliable datasets.</li></ul><p><br></p>
<p>We are looking for a dedicated Payroll Administrator to join our team. This is a Contract position, offering an excellent opportunity for a skilled individual with experience in payroll management. The ideal candidate will excel in handling payroll processes, ensuring compliance with regulations, and providing exceptional support to employees regarding payroll matters.</p><p><br></p><p>Responsibilities:</p><p>• Process weekly payroll for employees with accuracy and timeliness.</p><p>• Maintain and update payroll records, including new hires, terminations, salary adjustments, and deductions.</p><p>• Verify and reconcile timekeeping data, resolving any discrepancies promptly.</p><p>• Ensure compliance with federal, state, and local payroll regulations.</p><p>• Prepare and submit payroll tax filings and reports in a timely manner.</p><p>• Address employee inquiries related to pay, deductions, and tax withholdings professionally.</p><p>• Collaborate with HR and Finance teams on benefits, garnishments, and other payroll-related issues.</p><p>• Generate detailed payroll reports for management and auditing purposes.</p>
<p><strong>Position Summary:</strong></p><ul><li>We are looking for a Data Operations Engineer to support and oversee the automated data‑pipeline environment built on AWS. This position bridges data engineering and customer operations, ensuring that incoming datasets are processed accurately, consistently, and securely within established ingestion and transformation frameworks.</li><li>Key responsibilities include monitoring automated workflows, troubleshooting processing failures, validating data quality, and helping onboard new customers by aligning their data formats to a standardized internal model.</li><li>The role requires strong proficiency in SQL and Python, practical experience with AWS services, and the ability to communicate effectively with external customers when data issues arise.</li></ul><p><strong>Responsibilities:</strong></p><p><strong>Data Pipeline Monitoring & Operations:</strong></p><ul><li>Monitor automated batch and streaming data pipelines in AWS</li><li>Identify, troubleshoot, and resolve data processing failures</li><li>Investigate file‑level errors, schema mismatches, and transformation issues</li><li>Perform root‑cause analysis and document resolutions</li><li>Ensure data integrity, completeness, and timeliness across environments</li><li>Escalate architectural or systemic issues to the Data Engineering team</li></ul><p><strong>Customer Data Onboarding & Implementation:</strong></p><ul><li>Collaborate directly with customers to understand their file formats and data structures</li><li>Create and maintain mapping templates to align customer data to a normalized data model</li><li>Validate sample files and run tests on ingestion workflows</li><li>Configure ingestion parameters within predefined frameworks</li><li>Support customer go‑live processes and initial data processing cycles</li></ul><p><strong>Data Quality & Continuous Improvement:</strong></p><ul><li>Write SQL queries to validate data accuracy and research anomalies</li><li>Develop lightweight Python scripts for validation, transformation checks, or automation tasks</li><li>Improve monitoring processes, internal documentation, and operational playbooks</li><li>Work with engineering teams to strengthen platform reliability and observability</li></ul><p><strong>Customer & Cross‑Functional Collaboration:</strong></p><ul><li>Communicate clearly with customers regarding file issues or data discrepancies</li><li>Partner with internal teams including Data Engineering, Product, and Support</li><li>Provide feedback to enhance scalability, resilience, and overall platform performance</li></ul>