Head Of Big Data And Machine Learning Resume
- Successful Big Data Evangelist, Data Scientist and Analytics Champion, Disruptive Thinker and Thought - leader leveraging business, technology, management insights to transform business vision to business value. Hands-on technology leader who is mile wide and mile deep providing data monetization. Teach machine learning (part-time) at Columbia University. Built my own JVM (Java Virtual Machine). Worked with Dr. Ramnath Vaidyanathan on developing widely used R analytics packages - Shiny and knitr.
- Some summaries of his white papers/ presentations/ demos or talks can be shared on request.
- Well-known speaker at industry conferences like Strata-Hadoop, NAFIS, Tradetech, Columbia University and Harvard Business Club. Experience building profitable predictive data analytics products-whiteboard to launch.
- Working continually with C-level executives, very senior management on Big Data over Cloud, analytics.
- Led engagements from $3-120 mm spearheading next generation technologies.
- Built 30-60-90 day action plans/roadmaps and executed/blueprinted them for multiple firms to help reduce TCO.
- Leading Global Data Science programs, strategizing Big Data while building Digital Data Ecosystems with innovative solution in ML, chatbots and building AI teams with focus on data monetization.
- Delivered seven live big data implementations and 30+ POCs. Spearheaded multiple programs in AI and predictive analytics.
- Achieved business savings > 40 mm leading big data business strategy ideation and Data Lakes, data science, cloud initiatives for storage, risk management, regulatory reporting, valuation, analytics and fraud detection.
Messaging: Tibco, MQ Series, Webmethods, SeeBeyond, JMS, Kafka, Kinesis
NoSQL Databases and visualization tools: Vertica, Greenplum, Exadata, MongoDB, Redshift, Cassandra, Tableau, Pentaho, Qlikview, Datameer
Data blending: Paxata, Trifacta
Architecture /services: TOGAF, Zachman, EA, SOA, CostXpert, grid computing, SaaS, Cloud computing
Languages: R, Java, SAS, C++, VB, XML, C#, UML, C, SQL, WML, python
Data governance: Collibra, Alation, Informatica, Trillium, Adaptiv, Miosoft
Business Modeling: Provision, ARIS, Bwise, Fuego, Rational, RUP, RSA, UML, TogetherSoft, Requisite Pro
Methodologies: Agile, Scrum, RUP, CMMi, Waterfall, OOM, SOA, SDLC
Team collaboration: Jira, Confluence, bitbucket, bamboo, rally, Jenkins, github, Ansible, Devops, CI/CD
Strategy planning and execution, Executive team leadership, building analytics CoEs, jumpstarting and leading big data and data science teams, building strong relationships with businesses.
Head of Big Data and Machine Learning
- Nick is responsible for technology initiatives in a) IT launch of new insurance business products with visualization and reporting models b) strategically help business lines to achieve regulatory compliance c) manage costs via operational efficiency programs d) lead innovation initiatives in big data, reporting, analytics. Managing a team of 45+ global data scientists and big data with budget exceeding $20mm. Building a new focus on annuities- new line of business expansion.
- Provide senior leadership to build an integrated data-vision for the firm. Spearhead the strategic business and technology big data and data science initiatives for life, group and individual insurance programs.
- Champion data driven insights using machine learning, customer-centric analytics products. Led the asset management IT for Berkshire investments reporting-subsidiary.
- Define the robotic process automation for the individual markets.
- Responsible to build the big data and data science practice to 40+ members from 2 people. Spearhead the new end to end digital data ecosystem including real-time event ingestion, Hadoop data lake and predictive models for multiple datasets. Provide business value and monetization applying advanced analytics and data engineering techniques.
- Lead chatbots implementation team with AI and deep learning using api.ai, kore.ai and NLP delivering scalable solutions. Delivered click-thru analytics platform collecting usage from millions of mobile and websites to generate click-thru rates, conversion rates, purchase rates, insurance pricing models based on catalogue/media and search terms.
- Integrate data sets to help sales agents with real-time information for pricing competitiveness for claims, partner with vendors for innovative solutions related to customer data acquisition.
- Responsible for big data and predictive analytics models for-Reinsurance management, policy management, sales yield, claims optimization, customer cross sell, forecast simulation, call center, text to speech analytics, client segmentation.
- Research, prototype emerging technologies working with technology vendors to build innovative solutions.
- Developed the data strategy and roadmap for the cloud storage, security framework, big data analytics platform.
- Lead the big data migration to cloud and go-live initiative, data governance, enterprise data management.
- Strategized modeling-linear regression, MARS and SGBM, LDA machine learning algorithms implementation using R.
Executive Director, Enterprise Data Management and Big Data Analytics
- Member of the world recognized Confidential EMLP - Executive Management Leadership Program grooming new leaders.
- Conceptualize, envision and build the multi-generation targeted EDM strategy and roadmap using Big Data. Lead data analytics, streaming using Hadoop, Flink, Spark, Datarobot, Weka models.
- Lead the conceptualization to realization of big data and visualization, analytics framework for various Confidential umbrella companies. Strategize processing apps and calculation engines for Risk, Treasury, Finance, Commercial. Establish a data-driven culture with dashboard reporting, visualization and analytics.
- Socialize different machine learning and data science models with group CIOs and CDOs. Promote best practices in data management, analytics and machine learning AI.
- Partner with business teams from identification and prioritization of problems, building roadmap, framework and innovative solutions to communication of results ensuring business value is derived via analytics.
- Spearhead the roadmap and implementation strategy for data lake and analytics building a global team of 90+ resources. Led data science teams with real-time data prep, scoring and predictive models for 100+ ML algorithms and PB of data.
- Lead comparative analysis of automated machine learning models including datarobot, auto-weka, machine-JS, TPOT etc. Evaluate NLP technologies and build the team using technologies like SER, UIMA with companies like api.ai, angel.ai, mindmeld for sentiment analysis.
- Collaborate with MDs, business and technology stakeholders, operations bringing a change transformation and evangelizing technology acceptance.
Sr. Global Program Director-Big Data and Analytics
- Collaborate with IT leadership, senior management, business leaders and decision-makers to define target state big data architecture, PaaS framework, data science including data governance and integration.
- Build the data governance , master data management(MDM), metadata management and cross-BU customer analytics team to 22 people. Provide thought leadership on challenging problems with examples of implementing innovative analytic solutions and driving outstanding results.
- Commerce Model: Pioneer the 40 mm+ program from Discovery-to-Decision Making using operational insights with minimal latency via visualization and analytics. Lead development of a bi-temporal database, pioneer prime message bus, GRAIN, RICE risk and valuation engines with DSL.
- Spearheaded a patent-pending high speed caching engine directly serving millions of customers 10 times faster than before accelerating responses for trades STP.
- Build text analytics models using Arria, Yseop for sentiment analysis and text mining for wealth management
- Orchestrated the SDLC and PLC implementation initiatives for all ISGT and CTS programs-a global rollout.
- Was recognized for the pivotal role in realizing significant competitive advantage and unbeatable customer satisfaction from transformation of this magnitude.
- CFPS - Enhanced the customer fraud detection and risk protection system with 60+ global team members.
- Manage the global architecture team, formulate technology architecture, patterns and standards. Led effective use of dimensionality reduction, anomaly detection and clustering data science algorithms improving model accuracy to 80%.
Sr. Program Director-Big Data & Analytics
- Plan and execute the data science strategy. Pioneer the multi-million $Cornerstone Data Science Program for trading and transforming various asset classes using analytical modeling, correlation.
- Built trade capture and STP system recording 2.3B+ option ticks daily reducing TCO by 15 mm/year using a unique multi-scale simulation technique and AI models.
- Insights for valuation: Managed the big data investment recommendation and predictive analytics platform based on webtrends, research, hedge funds realtime data analysis, recommendations, social media, news channels etc. Major milestone reported by Wall Street Journal.
- Leveraged several sources of customer data transforming them into new products, upsell models, cross-sell models and other predictive algorithms to hedge funds and pension funds. Additional revenue generated=300 mm.
- Spearhead the global IT strategy for market, credit, operational, counterparty and liquidity risk. Manage valuations, pricing, quantitative risk management collaborating with business.
Vice President, Lead Strategist and Chief Data Architect
- Responsible for the strategy, implementation of risk management and real-time market data systems.
- Led development of trade analysis algorithms based on decision trees, random forest, logistics regression.
- Led the successful implementation of Molan-Mortgage and Loan analysis Datawarehouse system.
- Spearhead future state trading architecture for equities and fixed income. Led development of MDM - resulting in shared services model savings of $22 mm+. Built an Enterprise Data warehouse.
- Responsibilities included roadmap, development and implementation of real-time risk and pricing models, maintenance and development of analytical calculation framework.
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