Jobs and Careers
EX
Data Science Engineer, Lead Analyst, Enterprise Data & Analytics
Extreme NetworksMassachusetts, United States, United StatesRemotefull_timeVerifiedPosted 30 Dec 2025
About the role
Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.
Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.
Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.
Data Science Engineer, Lead Analyst, Enterprise Data & Analytics 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. Specific Duties:
Domain Experience · 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. Leadership Planning · 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.
Qualifications: Highly self-motivated and able to work independently as well as in a team environment.
Experience:· 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. Hard Skills · 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. · 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 Jir
Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.
Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.
Data Science Engineer, Lead Analyst, Enterprise Data & Analytics 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. Specific Duties:
Domain Experience · 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. Leadership Planning · 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.
Qualifications: Highly self-motivated and able to work independently as well as in a team environment.
Experience:· 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. Hard Skills · 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. · 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 Jir
Apply for this role
Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds.
Apply Now →Generate Application KitFree account required — sign up in 30s