Hello, my name is Syed Farhan Ahmed having 10yrs+ experience, and I am a highly motivated and skilled Data Scientist with a passion for learning and understanding data. I hold an IBM Machine Learning and Data Science Cer…
Hello, my name is Syed Farhan Ahmed having 10yrs+ experience, and I am a highly motivated and skilled Data Scientist with a passion for learning and understanding data. I hold an IBM Machine Learning and Data Science Certification from Coursera, which has provided me with a solid foundation in machine learning and data science concepts. My proficiency in Python, Pandas, NumPy, SciPy, NLP, SpaCy, Tfidvectorizer, Countvectorizer, Text Classification, Logistic Regression, Linear SVM, Decision Tree, Random Forest, Multi Class Classification, Neural Networks, RNN, ANN, CNN, Keras API, Tensorflow, Sentiment Analysis, and Voice Recognition has enabled me to develop a comprehensive understanding of data science techniques and tools.
I have a strong understanding of decision making, story telling and marketing strategies, which I believe are important in fulfilling the role of a Data Scientist. I am constantly seeking to improve my skills and am always eager to take on new challenges.
Generative AI with Langchain & SQL: Developed an application for internal stakeholders, improving operational efficiency and customer engagement.
OCR for Bank Account Statements: Implemented OCR technology to extract key financial information, enabling a swift and automated approach for assessing loan eligibility for new-to-bank customers, using bank statements as a pivotal requirement.
OCR for Account Opening Forms: Utilized OCR technology to capture data from account opening forms, integrating seamlessly with SUA API's to enhance the customer onboarding process.
Credit Card Logistic Regression Modeling: Executed a logistic regression model achieving a Gini score of 44, bolstering the bank's risk management by improving the predictiveness of credit card default.
Leading Team of 6 People: Enriching and enhancing every individuals capabilities to outperform the task which they have been assigned to. Rotate the task where necessary depending upon individuals skills and capabilities.
Cheque Deposit Kiosk OCR: This modeling with Azure OCR for various input features already mountain with core API's to call for validation and passing or failing the cheque this would be develop with front end application
Proficient in leveraging Google Cloud Platform and BigQuery for processing and analyzing large datasets.
Performed data cleaning and exploratory data analysis using Pandas, Seaborn, and R.
Developed predictive models using TensorFlow and LSTM neural networks for time series analysis and natural language processing.
Utilized Vertex AI and Jupyter Notebook within the GCP framework to build and deploy predictive models.
Used Looker Studio for effective visualization of complex data insights.
Used Dataform in GCP to manage and streamline the data pipeline from raw data ingestion to intermediate and output tables.
Bridged data from Full Circle ERP into BigQuery via SFTP server and automated pipelines on a daily basis with Google SSH.
Built a streamlined working dashboard of daily revenue via time series modeling.
Built a streamlined working dashboard of churn prediction modeling via KNN algorithm.
Built fully streamlined pipelines for Full Circle ERP to AWS to BigQuery and maintained tables via Dataforms and stored procedures where necessary.
Applied sentiment analysis video model into top 5 retail stores to take customer sentiments for gauging store performance.
Employed predictive modeling and analytics to forecast trends and patterns for data-driven strategies and decision-making processes within government agencies.
Used Tableau to create visual representations of complex datasets and communicate insights to stakeholders in the government sector.
Applied advanced statistical and machine learning techniques to large and varied datasets to support informed policy-making.
Developed a dashboard for Kamyab Jawan Youth Program.
Built a machine learning model for predictive Kamyab Jawan with KNN algorithm.
Developed a dashboard for Establishment with required parameters.
Used Microsoft Power BI for development of interactive and dynamic dashboards.
Integrated various data sources to create comprehensive and user-friendly dashboards.
Analyzed structured datasets to uncover meaningful patterns and correlations.
Organized, processed, and interpreted data to extract valuable insights for strategic planning and operational improvements.
Handled key European customers such as VF, with a focus on brands like Wrangler and Lee.
Oversaw the process from sampling to production and ensured client specifications were met.
Managed cut-to-pack operations for H&M, including trims and fabric.
Coordinated the supply chain process from sourcing materials to overseeing in-house processing.
Used ERP Oracle-based software for inventory management and process tracking.
Utilized software tools for planning, tracking, and managing inventory levels, order processing, and supply chain operations.
Developed an application for internal stakeholders using Generative AI with Langchain and SQL.
Implemented OCR technology to extract key financial information from bank account statements for assessing loan eligibility for new-to-bank customers.
Utilized OCR technology to capture data from account opening forms and integrated with SUA APIs to enhance the customer onboarding process.
Executed a logistic regression model for credit card default prediction, achieving a Gini score of 44.
Led a team of 6 people and rotated tasks based on individuals' skills and capabilities.
Developed a cheque deposit kiosk OCR model with Azure OCR and core APIs for validation and passing or failing cheques.
Provided credit risk modeling with logistic regression to the concerned business team.
Rolled out the first run for Gen AI modeling with SQL and engaged 3 people to test the model with prompt training.
Deployed churn modeling with KNN algorithm on a Power BI dashboard.
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