Ritik sharma

Data Analyst

Delhi, India0 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in building real-time data pipelines and dashboards.
Strong background in geospatial and environmental analytics.
Proficient in AI and machine learning for predictive modeling.

Stackforce AI infers this person is a Data Analyst specializing in Environmental Monitoring and AI-driven insights.

Contact

Skills

Core Skills

Data EngineeringMachine LearningData VisualizationGeospatial AnalyticsForecast AutomationAi DevelopmentData Management

Other Skills

AI AgentsAPIsAnacondaAnalyticsArtificial Intelligence (AI)Artificial Neural NetworksBig DataC (Programming Language)C++Chatbot DevelopmentCommunicationConvolutional Neural NetworksDashboard BuildingData AnalysisData Analytics

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Aurassure

2 roles

Data Analyst

May 2025 – Present · 1 yr 1 mo · Bhubaneswar, Odisha, India

𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 & 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: Designed and deployed real-time dashboards using Looker Studio, Streamlit, Plotly Dash, and Panel, hosted on Google Cloud VMs. Enabled cloud-based access to environmental insights by integrating live IoT and forecast data for internal and public stakeholders.
𝗚𝗲𝗼𝘀𝗽𝗮𝘁𝗶𝗮𝗹 & 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: Analyzed spatial-temporal pollution and climate data using QGIS, rasterio, geopandas, and netCDF4.
𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Automated ECMWF/CAMS data ingestion via Copernicus APIs to enable real-time forecasting pipelines.
𝗖𝗿𝗼𝘀𝘀-𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲 & 𝗣𝗿𝗼𝗮𝗰𝘁𝗶𝘃𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Proactively upskilled in out-of-scope technologies such as LLM, Google Earth Engine, Google Analytics, Django, Linux, and Cron Jobs to ensure project continuity during resource gaps. Took ownership of multiple data engineering tasks including pipeline maintenance, process automation, and task scheduling to ensure uninterrupted delivery of mission-critical insights.
𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝗮𝗹 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: Developed ETL pipelines for integrating IoT, satellite, and forecast data for urban monitoring.
𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Built a GenAI-based agent using Vertex AI & Gemini LLMs to generate SQL and visualize insights via RAG.
𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: Built ML models for prediction, anomaly detection, and time-series analysis on real-time sensor data.
𝗧𝗲𝗮𝗺 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽: Acted as a liaison between developer team and environment teams, helping align technical outputs with business objectives.
𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Presented actionable insights and trends to cross-functional teams and decision-makers, translating complex datasets into clear, impactful narratives using visual dashboards.

PythonSQLGoogle Cloud Platform (GCP)DjangoLooker StudioStreamlit+9

Data Analyst Intern

Oct 2024 – Apr 2025 · 6 mos · Bhubaneswar, Odisha, India

𝗖𝗹𝗼𝘂𝗱-𝗕𝗮𝘀𝗲𝗱 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗦𝗤𝗟 𝗼𝗻 𝗚𝗖𝗣: Designed and optimized complex SQL queries on Google BigQuery for processing and analyzing large-scale environmental sensor data, enabling real-time insights and efficient storage within cloud-native data architectures.
𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 & 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: Designed and deployed web-based dashboards using Streamlit, Plotly Dash, and Panel, hosted on Google Cloud VMs (Virtual Machines). These dashboards visualize real-time environmental data and forecasts, making insights accessible to stakeholders through secure, cloud-hosted platforms.

SQLGoogle BigQueryStreamlitPlotly DashData Management

National institute of technology rourkela

Data Scientist Trainee

Jun 2024 – Jul 2024 · 1 mo · Raurkela, Odisha, India · On-site

𝗔𝗽𝗽𝗹𝗶𝗲𝗱 𝗔𝗜 𝗳𝗼𝗿 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Developed predictive models using QNN, ANN, RNN, and CNN for tasks like air outlet temperature forecasting and thermal process optimization.
𝗗𝗮𝘁𝗮 𝗣𝗿𝗲𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 & 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: Gained hands-on experience in data collection, cleaning, and preprocessing for temperature-based volumetric analysis of chemical mixtures.
𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵-𝗗𝗿𝗶𝘃𝗲𝗻 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: Collaborated with faculty and researchers at NIT Rourkela's Mechanical Engineering Department, receiving mentorship in experimental design and advanced ML application.

Quantum Neural NetworkArtificial Neural NetworksRecurrent Neural NetworksConvolutional Neural NetworksMachine Learning

Royal statistical society

Member

Jan 2024 – Dec 2024 · 11 mos · London Area, United Kingdom · Remote

𝗔𝗰𝘁𝗶𝘃𝗲 𝗲-𝗦𝘁𝘂𝗱𝗲𝗻𝘁 𝗠𝗲𝗺𝗯𝗲𝗿 𝗼𝗳 𝘁𝗵𝗲 𝗥𝗼𝘆𝗮𝗹 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗦𝗼𝗰𝗶𝗲𝘁𝘆, gaining exposure to global trends in statistical science, data ethics, and quantitative research through journals and professional webinars.
𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗮𝗻𝗱 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 by engaging with RSS resources and events—supporting continuous learning in statistical modeling, inference, and applied analytics.