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Director Of Ai/machine Learning Resume

PROFESSIONAL SUMMARY:

  • Hands - on technical leader with a track record of building and growing data science teams.
  • Solving problems in ways that can be backed up with verifiable data (Text, Voice, Images, Videos and Numbers).
  • Mainly focused on driving processes, tools, and statistical methods which support rational decision-making.
  • Cultivating and growing talent to be capable of achieving outstanding results.
  • Help develop the creative atmosphere to innovate, while holding them accountable for making smart decisions and delivering results.
  • Customer obsessed and have sharp business acumen in product and consulting environment to build a service vision and roadmap that contributes to the success of organization.
  • Deeper understanding of AI, big data, analytics, & complex software engineering concepts.
  • Tech stack is a mix of batch and realtime, with Hadoop, Spark, Python, R, Scala and Crunch living alongside Cassandra, Hive and others with heavy Machine Learning, NLP/NLTK.

TECHNICAL SKILLS:

Analysis: Python, R, Matlab, Scala, SQL, C, Shell, NLTK/NumPy/SciPy/Pandas, GIS.

Big Data: Apache Spark, Hadoop, Hive, Cassandra, MongoDB, Databricks, AWS, Azure Cloud.

Machine Learning: Regression, Classification, Clustering, Collaborative Filtering, Recommendation Engine. Text Analytics regex, NLP, LDA, Cosine Similarity, Feature Extraction (Tagging and Parsing), Voice to text conversion.

EXPERIENCE:

Director of AI/Machine Learning

Confidential

Responsibilities:

  • Managing a Data Science portfolio of Data Scientist and Data Science Projects through Development, Delivery, Service Management and Support.
  • Providing technical and analytic direction, guidance and roadmap on ML projects. Deep technical expertise and strong problem-solving and data analysis skills.
  • A thorough understanding of machine learning based product development in a team and a strong track record of shipping products.
  • Identify new applications for machine learning across the company, clients and work with business partners to pilot Confidential or project.
  • Current Projects: Financial Transaction Forecasting; Facial Recognition System for Advertisement platform; Facenets Dataset for facial Recognition with 1M processed images.
  • Predict Fraud Customer using Historical Call Center Conversation; Energy Demand Forecast using Deep Learning; Content analysis platform using NLP, Equity Research (Stock Prediction) and Local Economy Forecasting; AI Leader (Recommendation System, Address Matching, Segmentation) for small businesses and vendors e-procurement system.

Principal Data Scientist & Senior Manager, Data Science Retail

Confidential

Responsibilities:

  • Data Science, Machine Learning, Personalization, Big Data
  • Develop data science strategy to increase sales of Confidential .
  • Develop real time ML and data processing models and architecture to process transactions and get insights using Microsoft Azure Cloud.
  • Design, develop and manage Data Science Products (Personalization, Customer Loyalty, Product Recommendation and Segmentation (targeted marketing) Engine).
  • Coordinate and communicate data and model amongst stakeholders throughout the Confidential, including product, engineering, marketing and business strategy teams.

Principal Data Scientist & Senior Manager, Data Science

Confidential

Responsibilities:

  • Data Science & Machine Learning Product Development & Management
  • Use deep and broad technical and management experience to complete hands-on technical work and provide leadership on complex product and business issues to engineering and business teams.
  • Design, development and management of Data Science and Machine Learning products (industry verticalization using LDA, Personalization (Cart Buster/Product attachment), Domain Recommendation using NLP, Customer Success Dashboard, Customer360 (Binary Feature Creation, Customer Segmentation, Churn, Next Product Buy) Confidential Small Business Success Index ( Confidential Patent), Competitor Intelligence Tool (Data Collection and matching with internal Product ID’s using cosine similarity)) for Marketing to grow Customer’s Life Time Value (LTV).
  • As a product owner define goals, set priorities for developing innovative features and AI (ML/DL/NLP) based products. Work closely with the Engineering/Platform and Marketing/Business teams to identify ML and Data Science opportunities to grow LTV and monetization of data and models.
  • Develop and enhance Machine Learning products and launch them on a regular basis as type I (final products) and type II ( Confidential ).
  • Drive awareness of Confidential ’s Platform in the market and engage with key influencers in Data Science community.

Senior Data Scientist & Senior Data Architect

Confidential

Responsibilities:

  • Responsible for delivering some of most strategic technical projects, deliver large scalable products, design new products as Confidential at the cutting edge of distributed technology.
  • As senior team member, owned the development effort of In-Memory Processing Confidential implementation using Apache Ignite and Apache Spark for credit card risk analytics for Amex Merchants in payment processing.
  • Predictive analytics using Apache Spark on credit card fraud data for volume and $ for 1,3,6,9,12 months with data assimilation capability.
  • As technical product manager, lead and guide team on development of ML toolkit for identification of consumer trends using merchant’s payment data, and behavior using Apache Spark.

Data Architect

Confidential

Responsibilities:

  • Lead the Machine Learning and analytics pipeline and API development efforts for Confidential Earth Analytics. Automated data ingestion and QA/QC pipelines to/from the federal agencies to Confidential .
  • Technical consulting for federal, state, vendor organization across multiple time zones and teams including Confidential ’s Product Management, Engineering, Design & Research, and other Data and Analytics Professionals to identify, build, and launch insightful tests.
  • Team member of Confidential project to design the Landsat satellite sensor architect; error analysis between different satellite systems. Developed statistical model to analyze error between observed measurements and predicted results.
  • Technical consulting for machine learning and data mining research, proposal writing creating proof of concepts on developing scientific machine learning models.

Research Data Analyst

Confidential

Responsibilities:

  • Developed information system for analyzing and visualization of large data (xml, json, hdf, txt, tiff) from IoT devices.
  • Developed Machine Learning algorithms (Regression & Classification) on large datasets (5 TB) for predictive analytics.
  • Developed optimization scheme using genetic algorithm for SWAP model.
  • Developed MATLAB based GUI for Numerical Methods for the Root Finding Problem; held workshops for attendees, created training material and manuals.

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