Lead Analyst, Data Science & Analytics
Extreme Networks
full-time
Posted on:
Location Type: Remote
Location: Remote • Massachusetts • 🇺🇸 United States
Visit company websiteSalary
💰 $110,000 - $125,000 per year
Job Level
Senior
Tech Stack
Amazon RedshiftAzureBigQueryInformaticaMySQLOraclePythonSQLTableau
About the role
- 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.
Requirements
- 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.
- 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.
- Highly self-motivated and able to work independently as well as in a team environment.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AI/ML model developmentpredictive modelingdata pipeline developmentfeature engineeringdata warehousingstatistical correlation modelsdata quality assurancemodel validationperformance monitoringnatural language processing
Soft skills
collaborationtechnical leadershipindependent workagile methodologycommunicationproblem-solvingself-motivationproject managementstakeholder engagementadaptability