07/20/2026 updated
100 % available
Data Analyst | Python | ML & AI | Automotive Domain
Coimbatore, India
Only remote
BE Automobile EngineeringAbout me
Hello! I’m Krishna, a Data Analyst and AI Engineer passionate about solving complex challenges with elegant, automated solutions. Skilled in data science, machine learning, Python scripting, workflow automation, and Discord bot development.
Artificial IntelligenceData AnalysisWeb ScrapingMachine LearningData ScienceData AnalyticsBotsDiscord
Programming (Python, R, SQL)
Advanced Python programming skills for large-scale data processing, reporting, and predictive diagnostics, complemented by proficiency in R and SQL for data analysis and querying.
Data Science & Predictive Modeling
Expertise in predictive modeling, data cleaning, validation, algorithm accuracy evaluation, and big data handling, applied to real-world diagnostics and fleet management solutions.
ML & AI (MLOps, Deep Learning)
Hands-on experience with supervised and unsupervised learning, deep learning, AI-based maintenance systems, and MLOps frameworks to deliver AI-driven solutions and firmware validation.
Automotive Domain Knowledge
Strong understanding of DTCs, telematics, firmware validation, fleet systems, and vehicle specifications, including DTC metadata pipeline management and manufacturer-specific standardization.
Data Visualization
Proficiency in visualization libraries including Matplotlib, Seaborn, and Plotly for creating insightful data representations and reporting.
Development Tools
Practical experience with tools such as Jupyter, VS Code, PyCharm, Git, Docker, Postman, and Excel (Advanced) for efficient development and collaboration workflows.
Cross-functional Collaboration & Pipeline Management
Experience owning and managing complete data pipelines, including enrichment, subsystem mapping, and standardization, while collaborating with cross-functional teams to deliver high-quality insights.
Electric Vehicle & Safety Systems
Project experience in building cost-efficient electric vehicles, designing safety braking systems, and developing drowsiness detection systems for automotive applications.
Advanced Python programming skills for large-scale data processing, reporting, and predictive diagnostics, complemented by proficiency in R and SQL for data analysis and querying.
Data Science & Predictive Modeling
Expertise in predictive modeling, data cleaning, validation, algorithm accuracy evaluation, and big data handling, applied to real-world diagnostics and fleet management solutions.
ML & AI (MLOps, Deep Learning)
Hands-on experience with supervised and unsupervised learning, deep learning, AI-based maintenance systems, and MLOps frameworks to deliver AI-driven solutions and firmware validation.
Automotive Domain Knowledge
Strong understanding of DTCs, telematics, firmware validation, fleet systems, and vehicle specifications, including DTC metadata pipeline management and manufacturer-specific standardization.
Data Visualization
Proficiency in visualization libraries including Matplotlib, Seaborn, and Plotly for creating insightful data representations and reporting.
Development Tools
Practical experience with tools such as Jupyter, VS Code, PyCharm, Git, Docker, Postman, and Excel (Advanced) for efficient development and collaboration workflows.
Cross-functional Collaboration & Pipeline Management
Experience owning and managing complete data pipelines, including enrichment, subsystem mapping, and standardization, while collaborating with cross-functional teams to deliver high-quality insights.
Electric Vehicle & Safety Systems
Project experience in building cost-efficient electric vehicles, designing safety braking systems, and developing drowsiness detection systems for automotive applications.
Experience
Professional experience0 - 5 years
Freelancer since2023
Languages
EnglishFluent
Project history
Working in the RNA Analytics Team focused on AI-powered fleet management and predictive maintenance solutions. Developed and automated over 90% of RNA's Python scripts for large-scale data processing, reporting, and predictive diagnostics. Owned and managed the complete DTC metadata pipeline including enrichment, subsystem mapping, and manufacturer-specific standardization. Performed model fitting for air intake diagnostics and evaluated algorithm accuracy for battery voltage, fuel level, coolant temperature, fuel trim, and fuel rail pressure. Collaborated with cross-functional teams using Python, R, SQL, and MLOps frameworks to deliver AI-driven solutions and improved fleet performance through real-time monitoring.