# Karthik D

> With Over 5 Years Of Experience | Data Analyst | Driving Smarter Decisions Through Data | Healthcare & Banking Expertise | Python | SQL | Power BI | Tableau | Open to Fulltime & W2 Roles.

Location: Fort Wayne, Indiana, United States
Profile: https://flows.cv/karthikd

I am a data-driven problem solver with 5+ years of experience turning complex datasets into clear strategies that drive growth, efficiency, and smarter decisions across healthcare, banking, and IT. My expertise spans Python, SQL, R, Tableau, Power BI, and cloud platforms (AWS, Azure), where I’ve built automated dashboards, predictive models, and scalable data pipelines that have cut costs, reduced risk, and improved customer and patient outcomes.

What sets me apart is my ability to translate raw data into business impact—reducing fraud losses by double digits, streamlining reporting cycles from weeks to days, and uncovering insights that have saved millions in operational costs. I thrive at the intersection of technical depth and business understanding, collaborating with executives, clinicians, and risk teams alike to make data accessible, actionable, and results-focused. Beyond delivery, I enjoy mentoring peers and fostering a data-first culture that empowers organizations to continuously learn and adapt.

## Work Experience
### AI Engineer / Machine Learning Engineer @ Seagate Technology
Jan 2024 – Present
•	Build and productionize machine learning solutions end-to-end, including data preparation, feature engineering, model training, evaluation, deployment, and lifecycle management within enterprise-grade environments.
•	Develop and tune deep learning and classical ML models for predictive intelligence use cases (e.g., anomaly detection, forecasting, pattern recognition), emphasizing reproducibility, reliability, and controlled releases.
•	Implement MLOps pipelines for continuous training and deployment using tools such as MLflow, containerization, and CI/CD practices, ensuring consistent model packaging, versioning, and rollout across environments.
•	Deploy inference services through API-based serving and batch scoring workflows, integrating with upstream/downstream systems while maintaining latency, throughput, and operational observability requirements.
•	Establish monitoring practices for model performance and data drift, improving ongoing model health through automated checks, alerting, and periodic retraining triggers aligned to production behavior.
•	Collaborate closely with engineering and stakeholder teams to translate requirements into measurable ML deliverables, documenting assumptions, limitations, and evaluation logic to support auditability and long-term maintainability.

### Machine Learning Engineer / Deep Learning Engineer @ Mastek
Jan 2020 – Jan 2022
•	Designed and delivered ML solutions for enterprise applications, owning modeling workflows from problem framing and dataset creation through training, validation, and deployment readiness.
•	Built predictive models for classification, regression, and time-series forecasting, improving model generalization through robust feature engineering, cross-validation strategies, and careful metric selection.
•	Implemented NLP pipelines for text classification and document processing, applying tokenization/embedding strategies, model tuning, and error analysis to improve accuracy and reduce failure modes in real data.
•	Operationalized models by standardizing experimentation and packaging practices (tracking experiments, managing artifacts, and ensuring reproducible training runs) to support reliable handoffs into production.
•	Improved ML delivery velocity by introducing structured evaluation workflows, automated training runs, and deployment checklists that reduced rework and made releases more predictable for engineering teams.

### Data Analyst @ Allsec Technologies Limited
Jan 2019 – Jan 2020
•	Supported development of ML capabilities by preparing datasets, performing exploratory analysis, and implementing baseline-to-intermediate models while aligning solutions to business constraints and available data quality.
•	Implemented supervised/unsupervised learning approaches and improved model outcomes through feature engineering, preprocessing pipelines, and repeatable evaluation using standard metrics (precision/recall/F1/AUC).
•	Built automation scripts in Python and SQL to streamline data preparation and training workflows, reducing manual effort and improving consistency across experiments and model iterations.
•	Assisted in validation and testing of models prior to deployment, supporting packaging, dependency management, and controlled execution in non-production environments.
•	Collaborated with senior engineers to debug model behavior and improve stability, focusing on data leakage prevention, overfitting controls, and clear documentation of assumptions.

### Machine Learning Intern @ Allsec Technologies Limited
Jan 2018 – Jan 2019
•	Built foundational ML models using Python and scikit-learn, working through the full workflow of data cleaning, feature engineering, training, validation, and performance reporting.
•	Assisted in dataset preparation activities (labeling/cleanup), improving the usability of training data and reinforcing disciplined practices around data quality and reproducibility.
•	Evaluated multiple modeling approaches and improved performance through tuning and error analysis, learning how to identify root causes of misclassification and instability.
•	Contributed to proof-of-concept ML work by implementing small modules and experiments under mentorship, translating requirements into working prototypes and measurable outputs.


## Education
### Master's degree in Information Science/Studies
Indiana Institute of Technology

### Bachelor's degree in Computer Science
Jawaharlal Nehru Technological University


## Contact & Social
- LinkedIn: https://linkedin.com/in/karthikd849

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Source: https://flows.cv/karthikd
JSON Resume: https://flows.cv/karthikd/resume.json
Last updated: 2026-04-17