Monika Suresh Gautam

About Monika Suresh Gautam

As a Data Science Practitioner with over 5 years of experience and a recent background in corporate finance, I am skilled in developing AI applications for various industries using both traditional and cutting-edge technologies. My demonstrated ability to collaborate with cross-functional teams, including DevOps, SDE, and Operations, to deliver end-to-end solutions has been key to the success of many of my projects.My expertise in leveraging Machine Learning, Deep Learning, NLP, and statistical methods to transform businesses and drive innovation has helped me build a reputation as a highly effective data science professional. I have experience in building predictive models such as Arima, Fbprophet, UCM, Exponential Smoothing, Moving Average, and have also built AI models such as Chatbots, NLP models, and Image recognition models using TensorFlow and Keras.My educational background includes a Master of Science in Business Analytics in Finance from The University of Michigan, Dearborn, MI, a Master of Engineering in Software Engineering from Ramaiah Institute of Technology, Bengaluru, KA, India, and a Bachelor of Engineering in Computer Engineering from Sarvajanik College of Engineering & Technology, Surat, GJ, India.I possess proficiency in programming languages such as Python, R, SQL, Cypher – Graph Query Language, and have experience working with databases such as Microsoft SQL Server, MySQL, AWS Redshift, and Neo4j. I am also skilled in frameworks and cloud platforms like Flask, Microsoft Azure, AWS (EC2, Redshift, S3), and front-end technologies such as HTML, CSS, jQuery, and Bootstrap.In addition, I am proficient in analytical tools such as Tableau, Power BI, Advanced MS Excel, Ilog Cplex, and LINGO. My passion for technology, coupled with my analytical skills, has driven me to excel in my field, and I am committed to continuing to push the boundaries of what is possible through data science.

Experience

1. Senior Business Analyst Consultant

   EXL

   Mar 2024 — Present · Pittsburgh, PA, US

   Leading fraud detection initiatives for digital banking and payment systems by leveraging Neo4j, GDS, Machine Learning, SQL, Python, and PySpark to uncover complex fraud rings and suspicious transaction patterns. • Designed and implemented an end-to-end Graph Data Science (GDS) pipeline using Neo4j for community detection, centrality analysis (degree, PageRank, betweenness), and link prediction. • Built visual fraud investigation workflows in Neo4j Bloom, enabling business investigators to intuitively explore transactional and entity-level fraud risks. • Collaborated with cross-functional teams to develop fraud rules based on subgraph similarity, recipient commonalities, and transactional motifs.

Education

• University of Michigan-Dearborn

  Master of Science - MS, Business Analytics in Finance

• Sarvajanik College of Engineering & Technology

  Bachelor’s Degree, Computer Engineering

  2011 — 2015

• Ramaiah Institute Of Technology

  Master’s Degree, Computer Software Engineering

  2015 — 2017

• Kendriya Vidyalaya

  High School, Science

  2009 — 2011

• Kendriya Vidyalaya

  Secondary School Certificate

  2008 — 2009