Machine can mimic humans in learning

Speech recognition, decision-making, and visual perception are some features that an ‘AI’ possess. The main goal of artificial intelligence has always been for these machines to be able to learn, reason, and perceive as human beings with little or no human intervention. But humans are always going to be needed to observe and supply equipment necessary to perform the processes.

Machines are driven by software packages that stores, sorts, processes complex datasets based on entities relationships feed by humans to perform event-driven actions that reduces human interventions.

AI enables an unprecedented ability to analyze enormous data sets and computationally discover complex relationships and patterns. AI, augmenting human intelligence, is primed to transform the scientific research process, unleashing a new golden age of scientific discovery in the coming years.

With artificial intelligence automating all kinds of work, we can think of a more comfortable future for ourselves that will create new jobs. According to a report on the Future of Jobs by World Economic Forum, AI will create 80 million new artificial intelligence jobs world wide by 2024.


Analytic Consultant


  • Lead and/or support development of hierarchical categorization taxonomies using NLP unsupervised/supervised methodologies including enrichment of unstructured data to derive themes and trends, with specific focus on early identification of emerging themes.
  • Develop non-model and model development to generate actionable insights and uncover patterns (structured or unstructured) from multiple sources, while working in partnership with teams across Conduct Management.
  • Perform text analysis and advanced analytics including using Natural Language Processing, Machine Learning techniques and programming languages to derive relevant analysis and metrics, including building proof of concepts to determine value of implementing in future projects.
  • Collaborate with team to develop data driven analytics capabilities to identify anomalies, outliers, emerging trends and conduct risks across the Enterprise. Primary areas of focus include Internal Fraud, Sales Practice, Ethics, and allegations
  • Collaborate with team to design complex projects/analyses generally spanning multiple products/business lines/functional areas/data sources including analytical application of industry-leading experimental techniques or exploratory data analytics to support teams across Conduct Management.
  • Partner with other Conduct Management and LOB stakeholders to develop, and enhance analytical capabilities related to Conduct Management’s first line of defense
  • Offer strategic recommendations to senior stakeholders and leadership based on thought-provoking and sound analytics including communicating technical and business details to ensure understanding.

Required Qualifications

  • 6+ years of experience in one or a combination of the following: reporting, analytics, or modeling; or a Masters degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis and 4+ years of experience in one or a combination of the following: reporting, analytics, or modeling
  • 2+ years of Python experience
  • 2+ years of Natural Language Processing (NLP) experience
  • 2+ years of statistical modeling experience

Desired Qualifications

  • Extensive knowledge and understanding of research and analysis
  • Strong analytical skills with high attention to detail and accuracy
  • Excellent verbal, written, and interpersonal communication skills
  • Experience with design, implementation and governance with Artificial Intelligence, Natural Language Processing or Machine Learning Architecture
  • Knowledge and understanding of analytical methods used in: statistics or predictive modeling methods (regression modeling, clustering, pattern recognition, graphics)
  • 2+ years of Tableau experience

Other Desired Qualifications

  • Model governance experience including writing model development documentation
  • Developing models to identify/detect emerging themes
  • Preprocessing (tokenization, part-of-speech tagging, parsing, stemming)
  • Semantic analysis (named entity recognition, sentiment analysis)
  • Modeling and word embeddings/representations (RNN / ConvNets, TF-IDF, LDA, Word2Vec)
  • Working with data science analytic tools (Watson Studio, Watson Discovery, IBM SPSS Modeler, Data Robot)
  • Experience with Tableau for data visualization
  • Expert ability to create compelling presentations in Power Point for executive level audiences
  • Experience in fraud, BSA/AML, investigations of financial crimes transactions or policy violations, risk management or compliance
  • Analytical and detail oriented with the ability to prioritize, execute and deliver projects on time
  • Strong desire and ability to independently solve problems and self-prioritize multiple tasks

Job Expectations

  • Ability to travel up to 10% of the time