Data Science Engineer, Lead Analyst, Enterprise Data & Analytics

Extreme Networks

1d • $110,000 - $125,000 • Remote

About The Position

The Data Science Engineer, Lead Analyst, Enterprise Data & Analytics will be a member of the “Expand” (Extreme Process Analytics and Data Governance) team, within the Data & Analytics pillar, and is responsible for developing and operationalizing AI/ML models that power predictive insights and automated narratives. This position is remote, reporting to the Director, Data and Analytics, and supports business stakeholders across all functions but be primarily aligned to Sales, Sales Ops, Marketing, and Finance.

Requirements

• Highly self-motivated and able to work independently as well as in a team environment.
• 3+ years of hands‑on experience in advanced analytics, data science, or AI model development.
• 2+ years of experience with more than 1 database system, such as Redshift, Azure Synapse, BigQuery, Oracle, SQL Server, MySQL, Snowflake.
• 2+ years of experience with more than 1 analytics/visualization tool, such as PowerBI, Tableau, Looker, Sigma Computing, or other BI reporting layers.
• Strong proficiency in building and deploying predictive models (classification, time‑series forecasting, regression, anomaly detection).
• Deep expertise in Python, SQL, Snowflake, data pipeline development, and designing and maintaining dbt models.
• Functional experience implementing a variety of data warehousing concepts and methodologies, including snapshotting, incremental data loads, SCDs, and star schemas.
• Can be highly flexible in adapting to the needs of the team and organization.
• Comfort in working within an agile team, leveraging DevOps concepts and agile-enablement tools including Jira, Confluence, and Github.
• Ability to clearly communicate complex project execution plans and technical ideas to both technical and business stakeholders, with demonstrated written and verbal presentation skills to present compelling recommendations.
• Comfortable working in a fast‑paced, high‑visibility environment with minimal supervision.

Nice To Haves

• Experience is a plus in (1) managing the ingestion and modeling of the following business application data sources: Salesforce, Oracle Suite (EBS, Fusion, HCM), and Jira, and (2) supporting analytical requirements for Sales, Finance, or Marketing teams.

Responsibilities

• Develop AI/ML models to generate both (1) predictive insights across a range of business functions, including, but not limited to, sales funnel forecasts, inventory drawdowns, back-end rebates, commissions, opportunity scoring, and “sales in” revenue, and (2) insight narratives to support executive summaries.
• Build and optimize AI-driven capabilities for “Ask EDNA,” supporting a search-like capability for metrics, dashboards, ad-hoc generation of metrics, and natural-language responses to business questions.
• Design and develop visualizations that present forecasted results and correlations.
• Build statistical correlation models leveraging 3rd party data to provide insight into sales and revenue trends benchmarked against external factors, e.g. market trends, tariffs, etc.
• Collaborate with cross-functional teams (Sales Operations, Finance, Marketing, Analytics) to understand forecasting and analytics requirements and rapidly translate them into production‑ready AI solutions.
• Design, implement, and maintain scalable data pipelines and feature engineering workflows using Snowflake and dbt.
• Ensure data quality, feature robustness, and model reliability through structured experimentation, model validation, and performance monitoring.
• Partner with peer members of the Analytics team in support of developing the end-to-end analytics solution using a modern technical stack, e.g. Snowflake, DBT, Fivetran, Informatica, Sigma.
• Assist in roadmap and planning activities to scope the level of effort for near- and long-term projects.
• Provide technical leadership in data science architecture and modeling best practices, AI enablement, and AI security and governance considerations.
• Independently manage personal backlog of work based on team’s priority, with escalation of interdependencies, collaboration opportunities, and potential blockers.
• Provide updates on progress, risks and mitigation strategies, milestones, and outcomes through the various agile meetings, including stand-ups, planning, refinement, and stakeholder readouts.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees