Data Scientist | Analyst Software Engineer
Afiniti
Total years of experience :10 years, 3 Months
Afiniti enhances human interactions in large enterprises by efficiently pairing customers with employees based on predicted interpersonal behavior.
Our applied artificial intelligence technology is generally applicable to the optimization of any interaction with the possibility of a selection between more than one people.
Currently we are focused on improving contact center interactions conducted over the phone, and we also provide optimizations for live chat, email, online video and in-person applications.
Our proprietary “big data” algorithms analyze client and third-party information to identify patterns of
successful and unsuccessful behavioral interactions. We then apply these patterns in real time to
augment human pairings and their associated commercial outcomes. We believe that our pairing
solution is unique, as it influences contact outcomes in a way not possible with traditional time-based,
utilization-based or performance-based methods of contact assignment.
Benessere is a startup non-profit entity focused on building health models through big data and utilizing digital devices such as the Microsoft Kinect to help drive down healthcare costs. Our vision is to educate the global community on sustainable health and wellness. Our mission is to challenge the traditional patient episodic care by focusing on proactive “personalized health wisdom.” We aim to detect, reduce and in some cases remove the impact of certain diseases through technology and activity based measurement.
A majority of Benessere’s research targets illness detection through symptoms that we can apply through vitals and activity based interventions. As part of this, Benessere is working with the Medical University of South Carolina, Sacred Heart University, while pursuing additional domestic and global partnerships. We look to increase better health and wellness applications by supporting hospitals/clinics that assist us in validating our models.
Automate Robotic Grasping to help people with constrained skeletal mobility in daily life activities. I worked as intern to build a Robotic arm, trained on visual cues and Kinematics data using machine learning algorithm Support Vector Machine.
• Application development for Skeletal data capturing of human chores through Kinect Xbox 360
• Serialize captured data(Data Extraction)
• Data labeling and clustering
• Machine Learning