AMIT JENA

Product Measurement Alignment Project with GCP and AWS Integration:Collaborated with Product teams across Experience Cloud solutions, leveraging cloud solutions such as GCP and AWS, to ensure alignment on product measurement strategies and goals.
Utilized cloud-based data storage and processing capabilities to efficiently collect, store, and analyze large volumes of data from diverse sources.
Implemented scalable data pipelines on GCP's BigQuery and AWS's S3 to automate data ingestion and transformation processes, enabling real-time monitoring of product performance metrics.

Dashboard Development and Analytics Enhancement using GCP and AWS Services:Led the development of interactive dashboards using visualization tools like Google Data Studio and AWS QuickSight, integrating data from GCP BigQuery and AWS S3 to track product performance metrics.
Leveraged advanced analytics capabilities of GCP's BigQuery ML and AWS's SageMaker to perform predictive analytics and identify trends and patterns in the data.
Collaborated with stakeholders to enhance dashboard functionalities, incorporating features such as dynamic filtering and drill-down capabilities to enable deeper insights into product performance.

Cross-Functional Execution and Adoption Initiative with GCP and AWS Integration:Orchestrated a cross-functional team to execute product measurement best practices across multiple Experience Cloud solutions, leveraging cloud services like GCP and AWS to streamline collaboration and data sharing.
Leveraged GCP's Data Studio and AWS's QuickSight to create unified dashboards that provide stakeholders with a comprehensive view of product performance metrics across different solutions.
Conducted training sessions and workshops to educate internal teams on cloud-based analytics tools and best practices for leveraging GCP and AWS services to drive data-driven decision-making.

Product Measurement Evangelism Campaign with Cloud Solutions Integration:Developed and executed a communication strategy to evangelize product measurement initiatives internally and externally, highlighting the role of cloud solutions like GCP and AWS in enabling scalable and efficient data analytics.
Created engaging presentations and case studies showcasing the benefits of cloud-based analytics solutions for measuring product performance and driving business growth.
Presented at industry events and webinars, emphasizing the advantages of leveraging GCP and AWS for product measurement and sharing success stories of organizations that have adopted cloud-based analytics solutions.

Problem-Solving and Initiative Demonstration with GCP and AWS Solutions:Identified and addressed key challenges in implementing product measurement strategies, leveraging cloud solutions like GCP and AWS to overcome obstacles related to data management, scalability, and performance.
Implemented cost-effective solutions on GCP's BigQuery and AWS's Redshift to optimize data storage and processing costs while ensuring high performance and reliability.
Demonstrated a proactive approach to innovation by exploring new features and services offered by GCP and AWS and proposing innovative solutions to improve data analytics capabilities and drive business outcomes.

• Conducted interviews with key business users to collect information on business processes and user requirements.
• Applied honed problem-solving skills to analyze and resolve issues impacting business operations and goal achievement.
• Analyzed open orders, backlog, and sales data to provide sales team with insights.
• Analyzed key aspects of business to evaluate factors driving results and summarized into presentations.
• Collaborated with Ministry of Health and Family welfare ,Govt of India to implement Artificial Intelligence projects in partnership with PGIMER Chandigarh ,AIIMS Delhi ,AIIMS RIshikesh
• Implemented AI Solutions at Centre Of Excellence ,Govt of India
• Lead team of Business Analysts,Data Scientist and Program to implement solutions at PGIMER Chandigarh

• Identified and documented detailed business rules and use cases based on requirements analysis.
• Researched and resolved issues regarding integrity of data flow into databases.
• Developed tables, views and materialized views using SQL.
• Designed and implemented tools to support strategic value chain optimization initiatives.
• Designed fresh executive dashboards using Powerbi/AAS model /SQL related to both verticals
• Lead the Marketing and conferences team in migrating dashboards and queries from Oracle Sql (P-SQL ) to Microsoft SQL Server (T-SQL
• Developed and maintained linkedin web scrapping code for gaining back lost seatholders which was further used by Data Engineering team to get data

• Worked with customers to understand needs and provide excellent service.
• Extracted data using queries to provide insights about customer experience eventually improving overall rating from 3.7 to 4.5
• Developed team communications and information for meetings.
• Participated in continuous improvement by generating suggestions, engaging in problem-solving activities to support teamwork.
• Resolved problems, improved operations and customer experience

• Synthesized current business intelligence data to produce reports and polished presentations, highlighting findings and recommending changes.
• Built library of models and reusable knowledge-base assets to produce consistent and streamlined business intelligence results.
• Transformed project data requirements into project data models.
• Participated in requirements meetings and data mapping sessions to understand business needs.
• Corrected any data entry error to prevent later issues such as duplication or data degradation.
• Coordinated statistical data analysis, design, and information flow.

• Assessing data quality and completeness(data Cleaning) for customer demographic and transaction data in preparation for analysis
• Identifying high-value customers to optimize resource allocation for targeted marketing based on customer demographics and attributes
• Used PowerBi to visualize sales marketing and growth strategy to clients and product managers.
• Completed 2 business projects

• Domain: Banking – Fraud Risk | Tech Stack : Python, Jupyter Notebook,Google Cloud AI Platform | Mar’20
• Objective: Building a Insurance RIsk fraud detection model for a bank
  Solution: Did EDA, treated data imbalance using SMOTE & ADASYN, built 7 models & did Hyper parameter tuning for best performing models in each category
  Key Achievements: ADABOOST on SMOTE oversampling having AUC,recall & precision of 0.94, 0.90, 0.99 respectively
• Domain: Stock Market | Tech Stack: MySQL | Nov 20
• Objective: To generate the data for Loan top up facility provided to
  customers.
  Solution: Implemented SQL Queries to define a user defined function which gave Buy/Sell/Hold signal on a given date via 10 days’ and 20 days’ moving averages
  Key Achievement: Successfully predicted behavior of stocks