Data Science with less than a year in Machine Learning & AI solutions.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Junior Data Scientist and AI/ML Engineer with hands-on experience in machine learning, deep learning, data analysis, and deployment of AI solutions. Skilled in Python, SQL, TensorFlow, FastAPI, and Streamlit with experience building predictive models, time-series forecasting systems, and LLM-based applications. Strong understanding of data preprocessing, EDA, model evaluation, and scalable AI workflows.
K.K Wagh Institute Of Engineering Education and Research
Bachelor of Engineering · Computer Science and Design
August 1, 2021 – June 30, 2025
Ai Varient
Data Scientist Intern
June 1, 2025 – March 1, 2026
India
Data-Driven Solar Power Forecasting Model
June 25, 2026 – February 1, 2026
• Trained and evaluated 3 machine learning models (Linear Regression, Random Forest, Gradient Boosting) using MAE, RMSE, and R2 metrics. • Processed and analyzed a dataset of 2,920 records, improving prediction reliability through model optimization • Reduced RMSE by 48% (6300 → 3302) compared to baseline Linear Regression • Achieved 89.6% R2 using Gradient Boosting, delivering high-accuracy regression performance.
Web Chatbot - Agentic AI
June 25, 2026 – April 1, 2026
• Designed a stateful AI chatbot using LangGraph with graph-based workflows enabling multi-step reasoning and context-aware conversations. • Integrated external tools (real-time web search APIs) with conditional execution to enhance response accuracy and dynamic decision-making.
View ProjectForecast Fusion - Time-Series
June 25, 2026 – May 1, 2026
• Benchmarked ARIMA, Prophet, LSTM, and XGBoost across 43 states with RMSE-based optimization. • Processed 8,084 time-series records (2019-2023) with lag-feature engineering and cross-state validation. • Reduced forecasting error by up to 95% in high-variance states, achieving 65% average RMSE improvement via automated model selection. • Deployed the end-to-end forecasting pipeline via FastAPI for scalable API-based inference.
View ProjectOracle Generative AI Certification
Oracle
October 1, 2025 – Present
Data Science Certification
ExcelR
October 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from solar power forecasting to time-series analysis and AI chatbots, indicates a broad interest in various data science applications. Their proactive pursuit of certifications (Data Science, Generative AI) and continuous learning aligns well with a culture of innovation and self-improvement. The internship experience at 'Ai Varient' and the remote work setup suggest adaptability. The candidate's skills align well with a data science role that requires both model development and deployment capabilities. However, the experience level is entry-level, which might require more mentorship in a senior-level team.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and applying new technologies, as evidenced by their diverse project portfolio and certifications. Their experience in collaborating with cross-functional teams and translating business needs into data-driven solutions indicates good team collaboration potential. The focus on model optimization and error reduction in projects suggests a detail-oriented and results-driven mindset. However, the lack of completed psychometric or English tests makes it difficult to fully assess stress handling, advanced communication clarity, and professional language usage beyond what is presented in the resume.