Sahaana Venkat Senior Data Scientist
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Sahaana Venkat
Senior Data Scientist in Siemens
Have 6+yrs of exp in PowerBi, Data Science, AI, Gen AI, Python, R, Excel
Data science professional with over 5+ years of experience in data management, machine learning, NLP, data
visualization, deployment, process design and optimization, and a strong track record of profit generation.
Giving good training in PowerBi and AI tools in online mode and can give latest assignments based on market requirements. Having on the market requirement tools needed for PowerBi and AI Tools. Can able to teach AI tools and Power Bi from beginner to advance level.

Subjects

  • Python Beginner-Expert

  • Power BI Beginner-Expert

Experience

  • Senior Data Scientist (Oct, 2023–Present) at Siemens,Bengaluru
    Received appreciation for design and end-to-end implementation of inventory report analysis and forecasting model
    for the company’s complete region.
    • Reduced daily intervention report creation time by 70% through automation of financial report (data visualizations
    using Excel and Power BI).
    • Received appreciation for pioneering the creation of dashboards using Power BI, leading to a greater data security and
    complex Power BI query higher uptime.
    • Received appreciation for pioneering the creation of models in Snowflake and Talend ETL, leading to a greater data
    security and complex Power BI query higher uptime.
    • Boosted sales by 10% and increased market findability by 4% from data provided by BCG consultants and passing it
    through NLP model to identify less performing states and identifying ways to tap it’s potential in India.
    • Created a Chatbot application in Python using NLP to filter the queries related to cement kiln operations and
    restraining from sharing of any confidential information as per the guidelines of the Online Data Protection Act by the
    Indian Government.
  • Data scientist (Jun, 2023–Oct, 2023) at ELGI EQUIPMENTS LIMITED,Coimbatore
    Received appreciation for design and end-to-end implementation of inventory report analysis and forecasting model
    for the company’s complete region.
    • Reduced daily intervention report creation time by 70% through automation of inventory report (data visualizations
    using Excel and Power BI).
    • Received appreciation for pioneering the creation of dashboards using Power BI, leading to a greater data security and
    higher uptime.
    • Boosted sales by 25% and increased market findability by 15% by web scraping data from GEM Portal and passing it
    through NLP model to identify government bidding of compressors in India.
    • Boosted sales by 10% and increased market findability by 4% from data provided by BCG consultants and passing it
    through NLP model to identify less performing states and identifying ways to tap it’s potential in India.
    • Created a Chatbot application in Python using NLP to filter the queries by the employers to prevent them from sharing
    confidential information against the company’s policy by automatically masking the figures related to the organization
    and pass the query to AI applications like ChatGPT in real-time.
  • Data scientist (Feb, 2023–May, 2023) at AKESO AND COMPANY, LONDON
    Received appreciation for design and end-to-end implementation of web-scraping of data for a UK based company.
    • Received appreciation for pioneering the creation of dashboards using Power BI and Tableau, leading to greater data
    security and higher uptime.
    • Analyzed the NHS supply chain trust supplier data and transformed it to a project requirement to handle the budget of
    assignment to different trusts and check product health.
    • Boosted sales by 20% and increased market findability by 5% by web scraping data from LinkedIn and passing it
    through NLP model to identify new prospect companies in UK and Europe regions.
    • Migrated important data from MS-Excel to Postgres and reduced data duplication by 60%.
    • Facilitated the development of accurate, error-free data models by complete data management of large data sets of
    size 500 to 1000 GB (from data cleaning preparing data using Python, SQL, and Excel).
    • Achieved 100% uptime by creating a VBA and deploying it using Docker created to run the demand intervention.
    • Carried out complete client needs analysis to deploy and develop Python models in Azure ML Data Lake and Docker.
    • Designed and developed Project document templates based on SDLC methodology.
    • Displayed excellence in Dimensional Data Modelling using Data modelling, Relational Data modelling, ER/Studio, Erwin,
    and Base & Dimensions tables, and Conceptual, Physical & logical data modelling
  • Data scientist (Mar, 2022–Nov, 2022) at BCA, LONDON
    Reduced daily intervention report creation time by 91.66% by automating the report (data visualizations using SQL,
    Shiny Tool and Power BI).
    • Played a key role in model creation, model maintenance, unit testing and code standardization, with a team of 25.
    • Led end to end data management – cleaning data to data preparation using Python, SQL, and MS-Excel.
    • Ensured high data accuracy, hence aiding the creation of car auction price prediction models by data scientists.
    • Leveraged critical thinking skills to accurately analyze business requirements and design ETL processes to load data
    from various sources like Flat files, XML files, Oracle Database.
    • Facilitated quick defect management by reviewing and prioritizing outstanding defects/system problems in Quality
    Center & Maximo, ensuring accuracy and deadlines were met.
    • Boosted team productivity by creating and updating the Data Dictionary Mapping from Database to User Interface (UI)
    for the Internal Portal Team.
    • Carried out bulk data transfer from external stage (AWS S3), internal stage to Snowflake, used snowsql to load data into
    snowflake tables, validated internal stage files, and transferred data between the two stages using various commands.
    • Provided support to data engineering team for deploying and developing Python models in Azure ML Data Lake.
    • Used AutoML Packages to develop and check the model performances.
  • Data scientist (Apr, 2019–Jan, 2022) at SIEMENS, MUMBAI
    Reduced operational costs for client by 20% by identifying the reasons for malfunction employing algebraic and
    statistical methods utilizing Python.
    • Utilized MLR, SPC, and Nelson's rules to detect anomalies in the preheater of cement industries using R to predict the
    occurrence of cyclone clogging in the cement preheater.
    • Automated production planning by designing data visualizations for business KPIs using SQL, Tableau and Power BI.
    • Carried out a complete analysis of cement kiln by employing Neural Networks, Time Forecasting, and AutoML
    algorithms using Python to prevent sudden breakdowns and optimize uptime.
    • Used Auto-encoder and DBSCAN method to identify anomalies in the wagon tippler mining industries using R to
    determine the location of potential issues in the wagon or track.
    • Enhanced the implementation of HSSE by performing video analysis using TensorFlow for identification and reporting
    of employees without helmets within the factory premises.
    • Created internal complex web API app services using Dot Net Core Entity Framework and React & Redux.
    • Created a KAIZEN reporting application using PHP and Bootstrap to reduce manual reporting.
    • Used LabVIEW and Power BI to design prototype dashboards for customers.
    • Received appreciation from manager for creating an Employee Leave Management Analysis tool using Python and PHP
    for effective shift planning and for keeping track of employee attendance.
  • Engineer (Jul, 2017–Mar, 2019) at ZF WIND POWER, COIMBATORE
    Digitized a process by creating an android application for digital autonomous maintenance system using C#.
    • Gathered data on integration issues and vulnerabilities and reported findings, including improvement recommendations.
    • Collecting data from machines with the help of LabVIEW, Modbus.
    • Created a desktop application using Dot Net (.NET) and developed macro files for automatic report creation
    • Created a Power BI dashboard to provide organization level data visibility of the KPI factors.

Education

  • Post Graduate Diploma (May, 2018–May, 2019) from IIITB Bangalore
  • Engineering in Mechatronics (Jul, 2013–Apr, 2017) from Anna University

Fee details

    ₹500–1,000/hour (US$5.90–11.79/hour)

    The price is negotiable

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