Lalit Kailas Hire
Data ScienceAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science with less than a year in AI/ML workflows and spatio-temporal forecasting.
Data Science graduate with a research focus in spatio-temporal forecasting, multi-source geospatial data fusion, and applied machine learning. Developed systems that integrate satellite observations, reanalysis, terrain, and ground-truth data into interpretable ML models. Secured All India Rank 6 at Smart India Hackathon 2025 (ISRO) for air quality forecasting, and built a publicly accessible policy simulation platform now in active use. Proficient in Python, SQL, XGBoost, LightGBM, ConvLSTM, Hugging Face, and cloud-based ML pipelines on AWS.
Savitribai Phule Pune University
Bachelor of Science (Honors) · Data Science
August 1, 2023 – June 30, 2027
Edunet Foundation (IBM SkillsBuild + Microsoft Elevate Program)
Artificial Intelligence & Machine Learning Intern
January 1, 2026 – March 1, 2026
India
Infosys Springboard 6.0
Data Visualization & Analytics Intern
September 1, 2025 – December 1, 2025
India
Terrain-Aware ConvLSTM for Site-Specific Wind Speed Forecasting
June 17, 2026 – Present
Built a terrain-aware ConvLSTM framework for site-specific wind speed forecasting across 5 wind-energy sites in Maharashtra. Processed 20 TB of multi-source data on AWS, integrating 15 years of ERA5 reanalysis, WRF meteorological outputs, SRTM elevation, and ESA WorldCover land-cover layers. Designed a 5 × 5 spatial grid with 8-step lookback and 5-step autoregressive rollout to preserve local spatial structure during forecasting. Achieved MAE of 0.2042 m/s and RMSE of 0.3503 m/s over a 5-step horizon, outperforming TCN by 16.4% in MAE and 16.9% in RMSE.
AccessLens: AI-Powered Benefit Access Risk Simulator
June 17, 2026 – Present
Built a publicly deployed full-stack platform that simulates access friction in welfare schemes, replacing eligibility checks with barrier analysis. Developed a deterministic risk model and counterfactual engine to quantify access barriers across 56 personas, 72 schemes, and 8 barrier types. Implemented a diversity-aware ranking system and an AI explanation layer that surfaces transparent policy reasoning for decision support. Deployed with multilingual support and privacy-first simulation boundaries; scalable architecture serves NGOs, policy analysts, and institutions.
SAFAL: AI-Driven Multi-Pollutant Air Quality Forecasting
June 17, 2026 – Present
Engineered a multi-source ML forecasting system for NO2 and O3 using 24-48 hour prediction windows. Processed ~1,039,390 INSAT satellite image crops and fused CPCB ground measurements, ERA5 reanalysis, and MERRA-2 aerosol products. Developed leakage-safe XGBoost models achieving PM2.5 RMSE ≈ 27.98 ± 5.34 µg/m³ and R2 ≈ 0.676. Secured All India Rank 6 at Smart India Hackathon 2025 (ISRO).
View ProjectIBM Data Science Professional Certificate
IBM
June 1, 2026 – Present
Mastering Generative AI & ChatGPT
Geeksforgeeks
June 1, 2026 – Present
Google Data Analytics Specialization
June 1, 2026 – Present
TechA Data Analytics using Power BI
TechA
June 1, 2026 – Present
Data Science Program – Relevel by Unacademy
Relevel by Unacademy
June 1, 2026 – Present
Google IT Automation with Python
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from welfare scheme simulation to air quality and wind speed forecasting, indicates a broad interest in applying data science to various real-world problems. Their academic background in Data Science and multiple certifications align well with a data-driven culture. The experience in both academic and internship settings, including a competitive national internship, suggests adaptability and a proactive learning attitude. The focus on interpretable ML models and transparent policy reasoning (AccessLens) also aligns with ethical AI development, which is a positive cultural indicator.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through complex data science projects. Their involvement in hackathons and publicly deployed platforms suggests initiative and a results-oriented approach. The ability to work with diverse data sources and integrate them into ML models indicates a structured and thorough operational fit for data-intensive roles. However, as an early-career professional, further development in leadership and stakeholder communication would be beneficial.