Senior Analyst supporting Used Vehicle Sales, Pricing, and Inventory strategy within the Finance Operations team, delivering analytical insights to enhance decision making, operational effectiveness, and financial performance.
Responsibilities
Analyze operational data to identify trends and opportunities for improvement.
Provide actionable insights to support decision-making for pricing and inventory management.
Partner with cross-functional teams to align strategies and optimize processes.
Facilitate collaboration between variable operations and departments such as marketing and sales.
Develop and maintain reporting tools to monitor key performance indicators (KPIs).
Requirements
Bachelor's degree in Business Analytics
Bachelor's degree in Data Science
Bachelor's degree in Economics
Bachelor's degree in a related field
Nice to have: Master’s Degree in a related discipline
A hands-on, results-driven Industrial Engineer to analyze and improve operational processes with a focus on efficiency, performance, ROI, and customer satisfaction.
Responsibilities
Analyze existing operational workflows, resource allocation, and key performance indicators (KPIs) within airport operations.
Collaborate with Operations and various Unifi teams to develop and validate performance improvement initiatives.
Identify inefficiencies and recommend process improvements to optimize throughput, reduce costs, and enhance service quality.
Develop models, tools, and dashboards to track performance, productivity, and progress of implemented solutions.
Support and lead implementation of process improvements, including on-site coordination, pilot programs, and feedback loops.
Requirements
Bachelor’s degree in Industrial Engineering or a related field
Build scalable data products, cloud-native data pipelines, and modern data platforms that support thousands of stores and millions of customer interactions.
Responsibilities
Design, develop, and support scalable data pipelines and data integration solutions.
Build data engineering solutions using Python, SQL, PySpark, and modern cloud technologies.
Develop and maintain trusted data products that enable analytics, reporting, operational intelligence, and AI use cases.
Contribute to enterprise data platforms built on Databricks, Apache Spark, and Lakehouse architectures.
Implement data quality, monitoring, testing, and observability capabilities to improve data reliability.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Computer Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field.
Nice to have: Hands-on experience through coursework, internships, research, personal projects, or open-source contributions.
Nice to have: Familiarity with cloud platforms such as Azure, AWS, or Google Cloud Platform.
Nice to have: Exposure to Databricks, Apache Spark, Delta Lake, Airflow, dbt, Snowflake, or related technologies.
Nice to have: Experience using Git and modern software development tools.
Lead and architect advanced analytics and machine learning solutions within the Microsoft cloud ecosystem to support strategic decisions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Principal‑level data scientist responsible for architecting, delivering, and governing enterprise‑grade advanced analytics and machine learning solutions in regulated healthcare environments.
Compensation
This role is compensated through a fixed annual salary. The expected salary range for this position is $170,000.00 – $180,000.00 annually, based on role scope, experience, and market considerations. This position is not eligible for bonus or incentive compensation.
Responsibilities
Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise‑level decision‑making across healthcare, operations, finance, and customer/member domains.
Own end‑to‑end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility.
Design analytics solutions natively within the Microsoft cloud analytics stack.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high‑impact, production‑ready analytics.
Requirements
Master's degree in data science, statistics, mathematics, computer science, engineering, or related field
Industrial EngineerNewUnifi
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