Help & Supportcareers@gravityer.com
Big Data Engineer || AI & ML . Automotive Geek .
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
global-energy-data-platform
May 4, 2026 – Present
Global Energy Data Platform is an Airflow‐orchestrated pipeline that ingests live energy price data from APIs, validates and cleans records, stores them in Postgres/MongoDB, and prepares features for machine learning. It enables reproducible workflows, daily updates, and future predictive analytics.
View ProjectF1-race-prediction-pipeline
April 30, 2026 – Present
An intelligent Formula 1 race outcome predictor that leverages historical performance, driver form, and constructor strength to forecast results. Built with modular ML pipelines and a FastAPI interface, it provides race insights, predictions, and monitoring for the current and past seasons
View Projectcrypto-classifier-
April 28, 2026 – Present
Script that connects to Binance API and retrieves OHLCV crypto market data. Converts raw JSON into a clean pandas DataFrame, casts timestamps and numeric fields, and saves results as CSV under data/raw/. Provides reproducible access to real trading data for downstream ML pipeline steps.
View ProjectHealthcare-ml-project
April 20, 2026 – Present
End-to-end healthcare ML pipeline: data cleaning, PostgreSQL storage, XGBoost model, FastAPI prediction endpoint, and Airflow retraining DAG.
View ProjectBinance_pipeline_airflow
March 31, 2026 – Present
A Dockerized Apache Airflow pipeline for cryptocurrency market analytics. The setup uses Postgres for metadata storage with Airflow orchestrating ETL workflows on Binance data. The project is designed to be modular, reproducible, , enabling automated ingestion, transformation, and scheduling of crypto analytics tasks in a containerized environment
View Projecthormuz_project
March 21, 2026 – Present
ETL pipeline for oil price volatility analysis using Python, Airflow, and PostgreSQL. Includes Grafana dashboards for visualization and modular scripts for reproducibility, supporting quant finance and risk modeling with a production‐ready workflow.
View Projectnairobi_property_pricing
February 17, 2026 – Present
A data pipeline for scraping, cleaning, and enriching Nairobi property listings. It normalizes prices, extracts bedroom counts from titles/URLs, and calculates per‐bedroom affordability. The project also generates location summaries and enriched datasets for analysis.
View Projectnse-stock-pipeline
December 18, 2025 – December 21, 2025
NSE Pipeline API is a FastAPI‐based backend service that delivers investor metrics and market insights for companies listed on the Nairobi Securities Exchange (NSE). It automates ingestion of daily price data into a Postgres database and exposes clean, production‐ready endpoints for frontend dashboards and investor tools.
View Projectbreast-cancer-pipeline
October 9, 2025 – October 21, 2025
A modular pipeline for ingesting and analyzing breast cancer diagnostic data using Python and PostgreSQL. Built for reproducibility, scalability, and real-world health impact.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards data engineering, machine learning, and backend development, primarily using Python. While these projects demonstrate strong technical capabilities, they do not directly align with a 'Frontend Developer' target role. The inclusion of 'typescript' and 'HTML' in one project ('hormuz_project') and 'HTML' in another ('nairobi_property_pricing') is minimal and does not indicate a primary focus on frontend development. This suggests a potential mismatch with the stated target role, though the candidate's ability to learn and adapt cannot be fully assessed without further information.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions indicate a focus on robust, reproducible, and scalable solutions, which suggests an analytical and structured approach to problem-solving.