We are your cultural GPS.

Pascalle is a Data-driven Creative Strategy Studio founded in Los Angeles.

Mission

To Move Culture

We help brands navigate culture to drive consistent impact through data driven insights.

The Pascalle Team

Cisco Robinson
Cisco RobinsonCEO & Founder
Cisco is the CEO and Founder of Pascalle. Previously he served as a White House Threat Analyst under President Barack Obama. He also architected and deployed a first of it’s kind Data & Analytics program for Target.
Anna Hughes
Anna HughesCOO
Data, analytics & insights consultant with x10 years of experience in digital marketing advertising and brand. Former Director of Analytics at Scotch & Soda, and Anomaly before that.
Daniel Patton
Daniel PattonFounding Member. Business Development
Daniel served as a technical consultant at Deloitte, where he helped execute digital transformation strategies across multiple industries, including insurance, government, and hospitality.
Nouman Khan
Nouman KhanPrincipal Engineer
Nouman has pioneered Computer Vision and Data Science solutions for a variety of global organizations. For the past 7 years he has dedicated his time towards finding solutions for Health Care, Sports Analytics and the Insurance industries. Seeking a new challenge he has chosen Pascalle, with the intent on building out an ethically sound ML vision.
Mahsa Raeisinezhad
Mahsa RaeisinezhadMachine Learning Scientist
Mahsa is a machine learning scientist with two master’s degrees—Mechanical Engineering from the University of Pittsburgh and Computer Science from Rowan University. Her expertise spans reinforcement learning, computer vision, and generative AI. She’s led AI efforts across startups and labs, with published work in robotics, nuclear systems, and autonomous vehicles.
Ahsan Akram
Ahsan AkramMLOps Engineer
Ahsan is a Senior MLOps Engineer with a Bachelor’s in Software Engineering and four years of specialized experience in Machine Learning, Python, and AWS Cloud operations. His expertise encompasses developing and deploying robust applications within Data Science, Computer Vision, NLP, and Data Mining, with a keen focus on innovation in MLOps and CNNs.

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