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Senior Data Scientist / Analytics Manager Resume

SUMMARY

Confidential Certified Professional with 11 years of Information Technology experience. Proficient in Requirement Analysis, Data Analytics, Predictive Modeling, Big Data, Computer Programming Languages, Strategic Planning, Team coordination and Project Management. Experienced in Client Interaction, User Training and Cross - Culture Team Environment.

TECHNICAL SKILLS

Data Analysis Tools: SAS 9.4, SAS Enterprise Miner, Hadoop, HDFS, HBase, HIVE, Sqoop, Flume, Avro, Pig, Spark, R Programming, MS Excel

Data Mining Algorithms: Linear Regression, Logistic Regression, Multinomial Logit, GLM, K-means, Support Vector Machine (SVM), Apriori, Naive Bayes Classifier, Random Forests, PCA, Factor Analysis, Bass Model, Conjoint Analysis, CRM - Lifetime Value Models, Survival Analysis and Hazard Models

Deep Learning Algorithms: Neural Nets, CNN, RNN, LSTM, RNTN, Restricted Boltzmann Machine, Autoencoders, Deep Belief Network, TensorFlow, Keras, Scikit-learn

Business Intelligence Tools: Oracle Hyperion FDMEE, Business Objects, ETL, SAP HANA, SAP NetWeaver BW, Tableau Programming languages - C, C++, Java, Unix Shell Scripting, Python (NumPy, Pandas, Scikit-Learn, SciPy), Scala, Perl, SQL Databases - Oracle 11g, MySQL, MongoDB, PostgreSQL, REDIS

Software Tools & Concepts: Artisan (Design, Analysis and Code Generation), MS Project Planner, openVZ, VM-ware, VirtualBox, DO-178B (Avionics Software Guidelines)

Configuration Management & Defect Tracking Tools: CVS, Clearcase, Git, Bugzilla, Jira, ClearQuest, Mantis

PROFESSIONAL EXPERIENCE

Senior Data Scientist / Analytics Manager

Confidential

Responsibilities:

  • Managed a team of 10 Data Scientists, which focused on improving the investment portfolio of a multinational financial services holding company
  • Worked on scoping and estimation of end-to-end data science solutions projects, inclusive of advanced models and analytics, to translate data-driven insights into actionable recommendations and outcomes for 5 fortune 500 clients
  • Designed, developed and coordinated predictive model for customer acquisition, for the marketing department of a major credit card provider in India with 70% reduction in marketing budget
  • Took an initiative to gain and understand customer data models and data architecture in a month, and trained 8 team members to increase the productivity of the project team to develop effective predict models
  • Coordinated improvements of data analysis models and project trainings across the business units reducing the ramp up costs by 70%

Senior Big Data Analytics Lead / Architect

Confidential

Responsibilities:

  • Defined data management, test strategies and best practices using Big Data technologies - Hadoop, HBase, Zookeeper, Hive, Spark, Sqoop, Flume and Avro
  • Designed, developed and coordinated Python API's for Peta byte structured and unstructured data to Hadoop Clusters with increased speed and efficiency of 30%
  • Ramped up a team of 10 engineers on Apache Spark, designed and developed a real-time data analytics model using MLib presenting customized forecasts for customers

Project Manager / Project Lead

Confidential

Responsibilities:

  • Spearheaded a team of 30 engineers within the account and managed 3 project deliveries
  • Proved pivotal in initiating the sub contracts, tracking and closing project deliveries successfully
  • Ensured effective account management, making strategies for effective retention of talented people in the account
  • Defined data management, test strategies, best practices and processes to improve effectiveness and quality of testing
  • Received customer satisfaction CSAT of 7/7 for this project

Project Engineer

Confidential

Responsibilities:

  • Responsible for Unit testing, Software Integration Testing, Hardware Software Integration Testing, System Testing and Test Automation for Commercial Aircrafts (DO-178B Design Abstraction Level A to E software systems)
  • Co-ordinated and actively engaged in system testing at client location in Germany with less than 1% defect slippage and effectively communicated the progress of system testing to off-shore managers

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