Data Scientist/ Data Analyst

Asghar K

.

Machine Learning Engineer

PROFESSIONAL SUMMARY

●Innovative Machine Learning Engineer with over 6.5+ years of experience in designing, developing, and deploying machine learning solutions that drive strategic business decisions and improve operational efficiency.

●9.5+ years of total IT experience.

●Extensive experience in machine learning model development, deployment, and maintenance.

●Proficient in Python for data analysis and machine learning implementations.

●Expertise in machine learning algorithms including linear regression, decision trees, SVM, k-NN, and ensemble methods.

●Strong knowledge of deep learning frameworks such as TensorFlow, Keras, and PyTorch.

●Experienced with natural language processing (NLP) and computer vision applications.

●Skilled in feature engineering and data preprocessing techniques.

●Proficient in creating robust predictive models, data mining, and advanced analytics across diverse industries including finance, healthcare, and retail.

●Demonstrated ability to lead cross-functional teams and manage projects from conception through execution.

●Skilled in leveraging deep learning, NLP, and big data technologies to solve complex problems, enhance user experience, and deliver actionable insights.

●Committed to staying at the forefront of AI technology through continuous learning and professional development.

●Proficient in using SQL and NoSQL databases for data storage and retrieval.

●Hands-on experience with cloud platforms like AWS, Azure, and Google Cloud for ML model deployment.

●Strong understanding of data structures, algorithms, and software engineering principles.

●Experienced with big data technologies like Hadoop, Spark, and Hive.

●Expertise in using version control systems such as Git and GitHub.

●Proficient in using Docker and Kubernetes for containerization and orchestration of ML applications.

●Strong knowledge of MLOps practices and tools for automating machine learning workflows.

●Experienced with A/B testing and model evaluation techniques.

●Excellent skills in data visualization using tools like Matplotlib, Seaborn, and Plotly.

●Strong problem-solving skills and ability to work with complex datasets.

●Effective communication skills for collaborating with cross-functional teams and stakeholders.

●Strong project management skills with experience in agile methodologies.

●Adept at writing and maintaining comprehensive documentation for ML projects.

●Committed to continuous learning and staying updated with the latest advancements in machine learning and AI technologies.

●Experienced in hyperparameter tuning and model optimization for improved performance.

●Proficient in implementing recommendation systems and personalized content algorithms.

●Skilled in anomaly detection and predictive maintenance techniques.

●Familiarity with reinforcement learning and its applications.

●Strong knowledge of statistical analysis and hypothesis testing.

●Experienced in collaborating with data scientists, data engineers, and software developers.

●Proficient in developing and maintaining scalable and efficient data pipelines.

●Expertise in using MLflow, Kubeflow, or similar platforms for tracking experiments and managing models.

SKILLS

●Programming Languages: Python

●Machine Learning Algorithms: Linear Regression, Decision Trees, SVM, k-NN, Ensemble Methods

●Deep Learning Frameworks: TensorFlow, Keras, PyTorch, LangChain, Keras, Hugging Face, Transformers

●Natural Language Processing (NLP): Text Processing, Sentiment Analysis, Language Modeling

●Data Visualization Tool: OBIEE, Tableau, Power BI

●Computer Vision: Image Classification, Object Detection, Image Segmentation

●Data Preprocessing: Feature Engineering, Data Cleaning, Data Transformation

●Databases: SQL, NoSQL, MongoDB, PostgreSQL

●Cloud Platforms: AWS, Azure, Google Cloud

●Big Data Technologies: Hadoop, Spark, Hive

●Version Control: Git, GitHub

●Containerization: Docker, Kubernetes

●MLOps: Model Deployment, CI/CD, MLflow, Kubeflow

●Testing and Evaluation: A/B Testing, Cross-Validation, Model Evaluation Metrics

●Data Visualization: Matplotlib, Seaborn, Plotly

●Statistical Analysis: Hypothesis Testing, Statistical Modeling

●Development Environments: Jupyter Notebooks, Anaconda

●Project Management: Agile Methodologies, Scrum

●Collaboration Tools: Jira, Confluence, Slack

●Optimization: Hyperparameter Tuning, Model Optimization

EXPERIENCE

Machine Learning Engineer

CVS Pharmacy, Oakland CA

Mar 2023 - Present

●Explored datasets to gain insights into the data distribution, identified patterns, and detected anomalies.

●Utilized Python and TensorFlow to build and train deep learning models for customer behavior analysis.

●Implemented data preprocessing techniques, including feature engineering and normalization, to enhance model performance.

●Cleaned and processed raw data to make it suitable for training models.

●Developed and deployed large language models (LLMs) for natural language understanding, improving customer interaction efficiency

●Developed NLP models to analyze customer feedback, helping the marketing team to better understand customer sentiments and preferences.

●Deployed predictive models on AWS EC2 instances, ensuring high availability and scalability.

●Trained the models using diverse datasets, optimizing hyperparameters to enhance model performance.

●Developed and trained machine learning models using appropriate algorithms and techniques.

●Experimented with different model architectures, hyperparameters, and optimization strategies to improve model performance.

●Developed and fine-tuned machine learning models using Jupyter, PyCharm, and Scikit-learn.

●Implemented robust data pipeline architectures to streamline data ingestion, processing, and storage.

●Collaborated with data engineers to ensure data quality and integrity across various data sources.

●Created new features to enhance the predictive power of the models.

●Conducted in-depth sales data analysis using Tableau and Power BI to uncover actionable insights.

●Used domain knowledge and statistical techniques to extract relevant information from the data.

●Worked on feature engineering and model tuning to enhance the performance of existing algorithms used within the platform.

●Evaluated model performance using appropriate metrics and validation techniques, such as K-fold cross validation.

●Used Grid Search to find the best combination of hyperparameters for a given model.

●Designed machine learning algorithms in VS Code to predict sales trends and optimize strategies.

●Integrated ML models into existing software systems or workflows with collaboration of software engineers and DevOps teams.

●Participated in training programs, workshops, conferences, and online courses to expand skills and knowledge.

ML/AI Engineer

Infosys, Dallas TX

Sep 2017 - Feb 2023

●Collaborated with product development teams to incorporate AI capabilities into existing and new products, enhancing product functionality and user engagement.

●Authored and maintained detailed documentation for machine learning algorithms, processes, and decision support logic for technical and non-technical audiences.

●Improved client website performance by implementing AWS services like CloudFront, RDS and Lambda.

●Validated migration through comprehensive testing, ensuring seamless transition and minimal disruption.

●Worked closely with data scientists, software engineers, and product teams to understand project requirements and deliver ML solutions.

●Collected, cleaned, and preprocessed large datasets to train language models, leveraging tokenization, data augmentation, and handling imbalanced data.

●Trained models using large-scale datasets, optimizing hyperparameters, and employing techniques like transfer learning and fine-tuning.

●Used TensorFlow and Keras in a Deep Learning project to predict whether a borrower will repay their loan.

●Developed a Question and Answer (Q&A) chatbot using LLM to enhance customer service and reduce the workload on human agents.

●Documented methodologies, processes, and findings. Reported progress and results to stakeholders, ensuring transparency and accountability.

●Participated in training programs, workshops, conferences, and online courses to expand skills and knowledge.

Scrum Master

Cintra USA, Dallas TX

Oct 2014 - Aug 2017

●Facilitated essential Scrum ceremonies, including sprint planning, daily scrums, sprint review, retrospectives, and stakeholder meetings, fostering collaboration and communication among team members.

●Identified areas for improvement through retrospectives, driving continuous process enhancements.

●Worked closely with cross-functional teams to translate business needs into robust analytic solutions by using advanced statistical and machine learning methods.

●Conducted data wrangling and preprocessing to prepare large datasets for analysis and model building.

●Collaborated with product owners and stakeholders to prioritize and refine the product backlog, ensuring alignment with business goals and maximizing the value delivered to customers.

●Successfully implemented machine learning models that improved client business processes showcasing significant enhancements in predictive accuracy and operational efficiency.

●Leveraged AI Prompt engineering to create value-based stories, enhancing customer satisfaction and ROI.

●Provided servant leadership, removing impediments, and promoting a culture of Agile and continuous improvement.

EDUCATION

Master of Science in Mechanical Engineering

Lamar University, Beaumont TX

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