Paxcom a leading Digital Solution Provider is a part of Paymentus now, a leading electronic bill payment provider. PaymentUs leads the North American marketplace in electronic bill payment solutions and have recently signed a partnership with Paypal and Alexa.
In this position, the AI/ML Specialist will work with stakeholders and technical
team members to deliver capabilities through agile acquisition, by leveraging
advanced latest technology.
Experience with Chatbot and NLP will be preferred.
Other key tasks:
Leverage knowledge of data science, methodologies, and processing
techniques to analyze vast amounts of chat data for monitoring & support.
Work with an agile team to develop machine learning analytics across
different domains where chat has been implemented.
Perform statistical analysis, data mining, temporal and pattern analysis,
correlation of events, predictive modeling, and pattern recognition for various
Document and visualize analytics both temporally and spatially, and present
analytic results and uncertainty to decision-makers.
Provide informational briefings to explain methodologies and analytical
findings to peers and customer stakeholders.
Investigate and implement new scientific analysis and methodologies to
support big data analytics efforts
REQUIRED EDUCATION AND EXPERIENCE:
Must have at least 2+ years relevant experience in Data Science /
BS, Master’s in data science, math, computer science, or a related
2+ years of machine learning experience.
Experience with machine learning and artificial intelligence techniques and
their implementations in open source technologies.
Experience in retrieving, manipulating, fusing, and exploiting multiple
structured and unstructured data sets from various sources.
Experience with analyzing large volumes of data using distributed
processing architectures with open source tools (e. g. Spark, Python, or R)
Ability to identify and analyze anomalous data (including metadata)
Ability to assess the feasibility of existing methods, models and algorithms
recognizing the capabilities and limitations of methods.
Ability to work in a small, mission-critical, DevOps team.
Ability to communicate and present analytics approaches and results
Level of experience (years):
Mid Career (2+ years of experience)