Infinite Uptime uses advanced predictive maintenance analytics and interconnected data to surface actionable insights. These insights empower intelligent, data-driven decisions, driving continuous improvement and optimizing performance with our predictive maintenance solutions.
We are looking for a highly adaptable and hands-on Data Scientist with at least 2 years of experience in machine learning (ML), deep learning (DL), and software development. The ideal candidate should be able to quickly understand industry structures, work with APIs, and build robust Python-based solutions that can be deployed as executable files or services.
· Industry & Data Understanding
o Quickly grasp domain-specific challenges and apply ML solutions effectively.
o Work with cross-functional teams to understand business needs and data flows.
· ML Model Development & Implementation
o Build, train, and optimize Machine Learning/Deep Learning models for predictive analytics, anomaly detection, and decision automation.
o Implement end-to-end ML pipelines from data ingestion to deployment.
o Handle large-scale data efficiently and develop automated processing scripts.
o Build robust datasets which includes labelling, dataset cleaning, Feature engineering, Exploratory Data Analysis.
· API & Software Development
o Develop Python-based APIs for model inference and data processing.
o Work with RESTful APIs, integrate third-party services, and automate workflows.
o Convert ML models into deployable, executable files for non-technical users.
· Fast Prototyping & Execution
o Write clean, optimized, and well-documented Python code quickly.
o Build functional proof-of-concept solutions under tight deadlines.
o Adapt to fast-changing business needs and iterate on solutions rapidly.
· Education:
o Bachelor's or master's degree in computer science, Data Science, AI, Machine Learning.
· Technical Skills:
o Strong Python coding skills with experience in fast development cycles (pandas, NumPy etc).
o Knowledge of ML/DL frameworks (scikit-learn, TensorFlow/PyTorch).
o Experience in handling APIs, web scraping, or automating data pipelines.
o Ability to convert ML models into standalone executables or deployable services.
o Hands-on experience with SQL for data extraction and manipulation.
o Familiarity with data visualization tools (Matplotlib, Seaborn, Plotly).
o Knowledge of cloud computing (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.
· Soft Skills:
o Ability to quickly adapt to new challenges and technologies.
o Strong problem-solving and debugging skills.
o Effective communication skills to work with technical and non-technical teams.
· Experience with MLOps tools (MLflow, DVC, GitHub Actions).
