Surendra Singh Devda

About Surendra Singh Devda

Product Manager, Managing JBT products, from machinery to digital machinery insights on OmniBlu dashboard.I have been deeply involved in the development and management of the OmniBlu software solution, particularly focusing on the Alert Management product. This advanced system is designed to efficiently manage alerts and alarms for machinery during production. By notifying business units and customers of potential issues—such as motor malfunctions, belt speed discrepancies, maintenance requirements, temperature fluctuations, or production breakages—OmniBlu plays a crucial role in ensuring seamless and safe operational processes. My work has significantly contributed to enhancing the reliability and responsiveness of our clients\' production environments.As a Azure Data Engineer into BridgeNext, We are responsible to build ETL pipelines with Python and deploy it on Azure, we have various function app which are deployed and automated using logic apps. Tools used into Azure are function app, Logic app, Service bus, Snowflake, Azure SQL db,Databricks, Pyspark.Earlier Data Engineer at Indium Software, I play with data and work on real-time analytics, high volume data ingestion, and anomaly detection. I use tools like Azure Pyspark Databricks, Alteryx for ETL operations, Postgre SQL for data validation, and Python for data processing and analysis. I have also created a Python API to download data from clients\' portals and load it to S3 (AWS).Prior to Indium Software, I was a Digital Marketing Analyst at Accenture, where I worked on the project of Spotify, running paid ads and analyzing the impressions and performance of the ads. I used tools such as Google Ads 360, Google Ads Manager, DoubleClick, and Creative Manager. I also have experience as a Data Science Intern at Flip Robo Technologies, where I worked on different data science projects, such as micro credit prediction, using logistic regression and hyperparameter tuning, and time series analysis, using ARIMA and SARIMAX libraries.I have a PG in Data Science and Neural Networks from DataTrained and a BE in Mechanical Engineering from All India Shivaji Memorial Societys College of Engineering, Pune. I have also earned certifications in Fundamentals of Digital Marketing from Google and Alteryx Certified from Alteryx. I am proficient in Python, MySQL, and Scikit-Learn, and have a keen interest in data engineering and data science. I am motivated by learning new skills, solving challenging problems, and creating value from data.

Experience

1. Technical Product Manager

   JBT Marel

   Jun 2024 — Present · Pune, IN

   JBT Marel is a leading global provider of integrated technology, equipment, and software solutions for the food and beverage industryJBT OmniBLU is a subscription-based digital service platform that uses AI and real-time data analytics to provide predictive maintenance, streamline parts ordering, and optimize the performance of JBT food processing equipment.I have been deeply involved in the development and management of the OmniBlu software solution, particularly focusing on the Alert Management product. This advanced system is designed to efficiently manage alerts and alarms for machinery during production. By notifying business units and customers of potential issues—such as motor malfunctions, belt speed discrepancies, maintenance requirements, temperature fluctuations, or production breakages—OmniBlu plays a crucial role in ensuring seamless and safe operational processes. My work has significantly contributed to enhancing the reliability and responsiveness of our clients\' production environments.Increased Production hours by 10% for customers and impact $18m ARR, through products that predict failures, prescribe optimum maintenance frequencies, reduce cleaning times and increase quality and throughput.Conducted and synthesized VoC interviews to identify pain points impacting user personas in food and beverage manufacturing.Have been leveraging AI predictive models to analyze similar data sets used by the Alert Management tool. By training and testing these models, we aim to deliver intelligent, proactive alerts to our customers and business units. This approach enhances the system\'s ability to anticipate and address issues before they escalate, thereby improving operational efficiency and safety.For achieving these smart alerts, models such as Random Forest, Gradient Boosting, or Neural Networks could be utilized due to their capability to handle complex datasets and deliver accurate predictions.

Education

• AISSMS College of Engineering

  Bachelor of Engineering - BE, Mechanical Engineering

  2015 — 2019

• DataTrained

  PG in Data Science and Neural Networks, Data Science

  2020 — 2021