I have over 9 years of experience in software design & development. Experienced at developing predictive models using various ML and data mining techniques to deliver actionable insights to businesses. Worked extensively…
I have over 9 years of experience in software design & development. Experienced at developing predictive models using various ML and data mining techniques to deliver actionable insights to businesses. Worked extensively with NLP for text mining and had exposure to Deep Learning for image recognition. I am looking for a senior position within data science & data analytics space.
Responsible for ensuring the accuracy and reliability of financial data by performing important tasks like data cleansing, including data normalization, identifying outliers, and filling in missing values.
Conducted exploratory data analysis to identify patterns, trends, and insights from financial datasets.
Applied statistical techniques and leverage data visualization tools to analyze financial data, enabling me to offer meaningful recommendations.
Effectively communicate complex analytical concepts to non-technical stakeholders and collaborate on data-driven projects to improve financial processes and outcomes.
Leveraging software development expertise to provide professional services focused on data analytics and model building.
Conducting data analysis and creating advanced models for projects.
Ensuring the accuracy and reliability of financial data by performing data cleansing.
Performing data normalization.
Identifying outliers.
Filling in missing values.
Conducting exploratory data analysis to identify patterns, trends, and insights from financial datasets.
Applying statistical techniques and data visualization tools to analyze financial data.
Offering meaningful recommendations.
Communicating complex analytical concepts to non-technical stakeholders.
Collaborating on data-driven projects to improve financial processes and outcomes.
Conducting quantitative analysis to obtain insights and develop workable solutions.
Following solutions through to successful delivery while measuring outcomes.
Training machine learning models using existing data.
Prototyping systems to test new approaches.
Using machine learning to identify anomalies in transactions to assist with fraud detection.
Developing dashboards for stakeholders that visualize data findings.
Implementing multi-phased text mining techniques to extract hidden information from drug safety datasets.
Providing timely responses to pharmacovigilance classifications using machine learning predictive algorithms.
Achieving over 90% accuracy with Logistic Regression and Decision Tree models.
Identifying adverse drug events and product complaints from a risk tendency using machine learning.
Developing an image processing model using CNN for medical imaging.
Deduplicating animal health records using pandas library.
Providing technical expertise as part of a team to develop and maintain clinical and pharmacovigilance systems.
Maintaining systems reliably with over 99% uptime.
Developing an automated process to restructure and streamline clinical data.
Providing faster insights to end users.
Standardizing ETL processes and tools to automate data extraction and manual reporting.
Reducing man hours across the entire operation.
Creating Regulatory Watch for news in the pharma sector using a web scrapping program.
Remodelling reports as per evolved database schema using Pandas and MySQL.
Producing and reviewing QA and Controls documentation.
Aiding the firm in getting ISO 9001 certified.
Creating eLearning training modules on Python, Data Analysis, Data Visualization, and ML.
Publishing an internal white paper on considerations to make while tuning ML models.
Utilising clustering and classification models for performing predictions in clinical trials.
Implementing NLP techniques such as Lemmatization, Stemming, Bag-of-Words, TF-IDF, and Word2Vec to examine drug related data.
Processing data using pandas to examine data.
Identifying patterns using statistical analysis.
Conducting EDA using Python, NumPy, pandas, and seaborn to derive insights from data.
Participating in all phases of the data mining project life cycle using CRISP-DM methodology.
Increasing model accuracy by 15%.
Utilising OpenCV for image processing.
Using morphological techniques, gaussian blur, and erosion.
Developing deep learning models (CNN and ANN) using TensorFlow and Keras framework.
Building a GUI application with Tkinter to return model output attributes for a given image.
Working in a team of 8.
Remodelling DB2 database.
Modifying existing programs.
Improving existing unit tests.
Designing and maintaining databases.
Fixing coding errors and other data related problems.
Identifying areas to increase efficiency and automation of processes.
Optimizing 5 million rows/day.
Improving load time by 95%.
Reducing manual effort by 60%.
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