Omni Reac

About the Role :

We are seeking highly motivated and analytical early-career engineers who are passionate about data, artificial intelligence, and problem-solving.

As a Junior AI & Data Engineer, you will gain hands-on experience working with real-world datasets, supporting AI/ML model development, and building scalable data pipelines.

This role provides an opportunity to learn directly from experienced Data Scientists and AI Engineers, laying a strong foundation in Data Science, Machine Learning, and Data Engineering practices.

Key Responsibilities :

- Assist in data acquisition, cleansing, transformation, and feature engineering to prepare datasets for machine learning and analytics projects.

- Develop and maintain Python-based ETL scripts for data extraction and processing using libraries such as pandas, NumPy, and scikit-learn.

- Support the development, training, and validation of supervised and unsupervised ML models (e.g., regression, classification, clustering).

- Build data visualizations and dashboards to communicate trends and insights using tools like Power BI, Tableau, or matplotlib.

- Work collaboratively with senior engineers to design and implement scalable data pipelines on cloud environments (AWS, GCP, or Azure).

- Participate in code reviews, documentation, and version control (Git) to maintain development standards and reproducibility.

- Continuously learn and apply emerging practices in AI model deployment, MLOps, and Data Engineering.

Required Skills & Qualifications :

- Programming : Strong proficiency in Python with experience using data libraries such as pandas, NumPy, and scikit-learn.

- Data & Statistics : Solid understanding of descriptive statistics, probability, correlation, and linear algebra fundamentals.

- Databases : Basic knowledge of SQL and relational database concepts.

- Analytical Thinking : Strong logical reasoning, problem-solving, and mathematical aptitude.

- Version Control : Basic familiarity with Git/GitHub workflows.

- Eagerness to learn and adapt to AI, Machine Learning, and MLOps technologies in a fast-paced environment.

Preferred Skills (Good to Have) :

- Exposure to cloud platforms (AWS, GCP, or Azure).

- Hands-on experience with data visualization or exploratory analysis (Tableau, Power BI, matplotlib, seaborn).

- Familiarity with REST APIs, Jupyter Notebooks, and scripting for automation.

- Participation in Kaggle competitions, academic AI projects, or open-source data projects.

- Passion for mathematics, data-driven problem solving, and continuous learning.