Data Engineer - NTT Data Australia
Master of Data Science - Monash University
I am a Data Engineer / Machine Learning Engineer by profession, with a Master’s degree in Data Science from Monash University.
My expertise includes working with large data sets to come up with analyses that are in line with the company’s goals. In my previous roles, I have been responsible for creating visualisations to communicate key business insights to shareholders from multiple different teams.
I excel at coming up with technical data solutions to help solve real-world business issues while effectively communicating these analyses, predictions, and ideas with the team and various shareholders to quickly come up with scalable prototypes to get a clear measure of growth.
Garnering work experience from the corporate firms of all sizes, I’m a critical thinker driven by the fascination of technology with an urge to create positive impact on businesses. Some of the domains I've worked in are Energy & Gas, Healthcare, Financial Services and Insuarance.
When I'm not breaking my head on fixing bugs in my code, you could find me playing Bass Guitar, playing Football or keeping upto date on Geo-politics. I am also deeply curious about the financial world, and actively invest in the growing Indian market.
Major - Big Data
Major - Data Science
Shiivong was a delight to manage. Always positive, hungry to learn and improve, his attitude was as good as one could hope for in a team member.
During his time with Mott MacDonald, Shiivong made great strides in transitioning the application of his fundamental technical knowledge from single use cases to scalable production-ready code that underpinned cloud deployments and unlocked high value outcomes for our infrastructure sector clients.
He made a significant and positive impact during his time at Mott MacDonald and will be missed.
Shiivong is an extremely proactive Data analyst with a good mix of technology and functional understanding.
I was extremely impressed by his effort and productivity within the team while working with him.
I wish Shiivong the best of luck with his future projects.
I rarely come across real talents who stand like Shiivong.
I had the pleasure of working with Shivong for product development, collaborating on several aspects of different tools.
His perseverance to handle such heavy lifting in earlier phases of his career made a huge impact on the faster solution development.
Process Mining being a niche skill set, he was able to grasp the subject and played a pivotal role in bringing the tool at a significant mature stage.
As a team member, Shiivong earns my highest recommendation, a stellar performer indeed.
Top notch attitude, great problem solving skills, ability to grasp things at drop of a hat and a fun person to work with, Shiivong brings a lot of dynamism, creativity and dedication to the table.
I worked with Shiivong for almost a year in very critical project of Healthcare services client for BI implementation. He learned SSIS, SSAS and Power BI in no time and started handling a critical module in project independently. He owned the module end- to- end, right from requirement gathering, logic/ source system understanding, implementing and designing dashboards. Shiivong received appreciation from all client senior/executive management for his amazing work for the executive dashboard.
Shiivong went out of his way and leveraged his R and Shiny skills to help a new solution development in KPMG analytics practice while handling the strict deadlines at client project deliverable. His contribution during nascent stages of the solution, helped team a lot to develop it further.
I wish Shiivong a very bright career and best wishes for his future endeavors.
Shiivong is a hardworking and professional person. He is a quick learner and has a right attitude towards learning.
He joined as an intern in KPMG and continued as analyst.
He independently completed 4 modules of a project with minimal issues.
He picked up MSBI skill in very short time and has good knowledge in SQL as well.
As a senior, I have reviewed his work and it was good to see that his work is praiseworthy.
Besides MSBI, he worked on R analytics side by side for process mining. Overall he is a good person.
• The Databricks Accredited Lakehouse Platform Fundamentals accreditation exam will test your knowledge about fundamental concepts related to the Databricks Lakehouse Platform. Questions will assess how well you know about the platform in general, how familiar you are with the individual components of the platform, and your ability to describe how the platform helps organizations accomplish their data engineering, data science/machine learning, and business/SQL analytics use cases. Please note that this assessment will not test your ability to perform tasks using Databricks functionality. Instead, it will test how well you can explain components of the platform and how they fit together.
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• Help collect enterprise-level requirements for data analytics solutions that include Azure and Power BI.
• Advise on data governance and configuration settings for Power BI administration.
• Monitor data usage.
• Optimize performance of the data analytics solutions.
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• Azure Data Engineer Associate certification validates the skills and expertise in integrating,
transforming, and consolidating data from various structured and unstructured data systems into
structures that are suitable for building analytics solutions. Candidates have a solid knowledge of data processing
languages, such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture
patterns.
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• Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies, translate words, and use locality-sensitive hashing to approximate nearest neighbors.
• Use dense and recurrent neural networks, LSTMs, GRUs, and Siamese networks in TensorFlow and Trax to perform advanced sentiment analysis, text generation, named entity recognition, and to identify duplicate questions.
• Use dynamic programming, hidden Markov models, and word embeddings to autocorrect misspelled words, autocomplete partial sentences, and identify part-of-speech tags for words.
• Use encoder-decoder, causal, and self-attention to perform advanced machine translation of complete sentences, text summarization, question-answering, and build chatbots. Models covered include T5, BERT, transformer, reformer, and more!
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• Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.
• Build natural language processing systems using TensorFlow.
• Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
• Apply RNNs, GRUs, and LSTMs as you train them using text repositories.
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• Co-authored a paper on Machine Learning on Imbalanced Data in Credit Risk, published in
an IEEE paper publication to address the problem of privacy in Data Mining and to suggest a
simple yet effective way to preserve the privacy by hiding the sensitive data before using Data
Mining algorithms.
To access the paper, See publication
• Co-authored a paper on Data Mining on factors that affect a students' performance at school.
To access the paper, See publication