Alec Avery
Lead Solutions Consultant at Sprinklr
- Role
- Lead Solutions Consultant - Large Enterprise at Sprinklr
- Location
- Pittsburgh, PA, US
- LinkedIn followers
- 500 followers
About Alec Avery
I work with large enterprise organizations to design and present AI-powered customer experience solutions that bring together service, social, marketing, and research in one platform. I get to blend storytelling with technical depth, showing how the right functionality and integrations can drive real business impact.Before Sprinklr, I led digital transformation initiatives at Booz Allen Hamilton, delivering implementations for federal clients like the IRS, Treasury, and VA. From low-code to custom implementations, I’ve guided Agile teams through end-to-end solution delivery — aligning stakeholders, optimizing data workflows, and simplifying complex integrations.
Experience
Lead Solutions Consultant - Large Enterprise
Jul 2025 — Present
Configure and demo customized solutions for enterprise customers, leveraging Sprinklr\'s AI-powered customer experience platform to address complex business challenges across customer service, social publishing/engagement, marketing, and research.• Collaborate with sales and consulting teams to integrate AI, LLM, and data science capabilities into client’s existing workflows.• Provide strategic guidance on data architecture, platform deployments, and API integrations.
Education
James Madison University
Bachelor’s Degree, Computer Information Systems
2014 — 2018
General Assembly
Data Science bootcamp where I advanced my technical skills in Python through data preprocessing, analysis, and machine learning projects – including an NLP capstone that predicted wine varietals from reviewer noted tasting notes. The course included the following content: • Data analysis and Data Visualization • K Nearest Numbers • Model Evaluation • Linear Regression • Logistic Regression • Advanced Classification Metrics with ROC • Naive Bayes and NLP • Decision Trees • Random Forest • Advanced Sklearn • Dimensionality Reduction - PCA • APls with Python K-Means Clusters • Time Series
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