Vidya Venkatesh

Enterprise Forecast as a Service (EFaaS):

• Worked with stakeholders to develop overall vision for the product based on impact, effort and test coordinations.
• Created causal graphs for walmart with various KPI's, Coordinated with teams to collect data and set up a feature repository for the same while ensuring compliance with walmart standards, mitigating risks associated with sensitive information handling.
• Collaborated cross-functionally with Sam's club team to onboard the Maestro to Walmart cloud environment.
• Solely developed and deployed Python API on WCNP (walmart cloud platform)
• Working on Feature store POC and Leading the harmonized WFP onboarding efforts to EFaaS

Harmonization :

• Leading the project which involves collaboration with stakeholders, ensuring alignment on key initiatives and project goals and mentoring team.
• Collaborated with stakeholders/other forecasting teams to gather the data and EDA for the POC
• R&D of "garage" forecasting analytics solution on the GCP to harmonize any forecast with IBG.
• Identified evaluation criteria to improve the forecasts for KPIs across business areas in correlation with IBG.

• Mentored and led the team on Data Science project initiatives and was responsible for driving the delivery of multiple projects at the same time.
• Developed time-series models and causal models for transportation team. Improving the model accuracy to 90% saving ~$25million for the company.
• Model Deployment & Scaling: Scaled analytical capabilities across the business area working in End-To-End Supply Chain Projects, with Pyspark, which reduced the pipeline SLA thus reducing overall cost.
• Data: Drove the effort to collect data by collaborating across different domains of walmart teams and worked with their SME"s to get the best possible data for analytics.
• Worked on detailed RCA for the leadership on the E-comm and MCSE data which lead to identification of savings pockets for the company.
• Provided comprehensive analysis and recommend solutions to address complex business problems and issues using data from internal and external sources and applied advanced analytical methods to assess factors impacting growth and profitability across bank's product and service offerings.
• Developed data-gathering and reporting structures from ground up, strategized methods capitalizing on system features and Analytics all on GCP (Google Cloud Platform).
• Proven record of working exemplary with tight deadlines and fast-paced atmosphere.

• Scaled analytical capabilities across the business area i'm working in (Fresh Produce from Distribution Centers to Stores), evolving analytics to influence Supply chain and logistics domain's strategic planning and executives' decision-making.
• Provided comprehensive analysis and recommend solutions to address complex business problems and issues using data from internal and external sources and applied advanced analytical methods to assess factors impacting growth and profitability across bank's product and service offerings.
• Applied statistical and algebraic techniques to interpret key points from gathered data.
• Collaborated with internal stakeholders, identifying and gathering analytical requirements for customer, product and projects needs.
• Gathered requirements and developed project plans.
• Developed data-gathering and reporting structures from ground up, strategized methods capitalizing on system features and Analytics all on GCP (Google Cloud Platform).

• Designed and developed Schema data models.
• Performed Statistical Data Analytics, design and information flow using Data Bricks (distributed platform) and Python Scripts. Documented all business workflows for stakeholders to review.
• Built Application platform foundation to support migration for client-server product lines to enterprise architectures and services.
• Developed data architecture design to enable myself and other Analysts to perform targeted customer analysis.
• Performed data visualization using python to enable non technical business users Identify areas that need attention or improvement during reviews.

Quantifiable results:

• Helping my team in capital one with my Analytical skills on what they can achieve with data they have and how beneficial that would be to business. The results after me joining, the team has seen a significant improvement in the change through ways-of-working.
• Got a great feedback and appreciation in the short time after joining capital one for performing data visualization. Visualization was one area where the team was behind. My expertise in this area provided much needed understanding to visualize the data and work more towards needs of end users.
  

• Designed intricate algorithms based on deep-dive statistical analysis and predictive data modeling and built a system to determine fault classification and location on the power grid using Machine Learning Techniques.
• Was responsible for extracting huge customer data from different servers using Spark-R and doing Sentiment-Analysis using NLP.
• Built a tool ,full stack, to view the historical data graphically for entire power distribution network.
• Designed and Implemented TAP - Technology Assessment process. TAP is a workflow built as web application which allows employees to assess new technologies and evaluate standards to be implemented in dominion.
• Developed a database schema with Entity Framework 6 to increase the efficiency of the queries.

Quantifiable results:

• Helped Dominion get rid of old ways of detecting the fault location. The new machine learning method gave the higher operational stability and reliability of the power system which resulted in avoiding huge power failure.
• Full stack tool/Dashboard that was built helped the higher management to visualize the historical data of the entire network with just a click on a button.
• TAP went live into production and has received a great feedback from the users on its ease of use and implementation. It has enabled employees to assess new technology and evaluate standards.
  
  

• Worked on verification and validation methods of the digital safety systems for nuclear power plants.
• White Paper titled "Assertion Based verification of EDG system" accepted at NPIC conference 2017.

Quantifiable results:

• Helped VCU to complete the projects they owned before time by contributing immensely on verification and validation methods.
• Worked on publishing the white paper for NPIC conference and thereby bringing a value add for the research work.

• Developed maps on SAP-PI to integrate and map the data flow between the systems.
• Collaborated with 4 functional teams across 4 countries to complete projects and achieve deadlines Apr'15- Apr'16, 

Quantifiable Results:

• Received 4 awards for developing automated tools which increased revenue by 10%.
• Elicited business requirements, transformed and documented design specifications for the client.

• Developed an instrument to help in increasing the accuracy of structural testing of the Aerial Vehicles.
• Worked as a member of three-person team developed efficient and economic instrument which cost 36% less than the current instruments available/ in use.

Quantifiable Results:

• The technology that was developed for accuracy of structural testing of the Aerial Vehicles.saved $250-$400 for HAL.