Jr. Machine Learning Engineer

IMMEDIATE JOINERS !! Junior Data Scientist: Machine Learning & Python Specialist with SQL We are seeking an innovative and results-driven Data Scientist with a strong focus on Machine Learning and deep proficiency in Python . You will be instrumental in transforming complex data into actionable insights, building predictive models, and driving business strategy using cutting-edge analytical techniques. Model Development & Implementation: Design, develop, train, validate, and deploy advanced Machine Learning models (e.g., Data Wrangling & Analysis: Perform comprehensive Exploratory Data Analysis ( EDA ), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets. Coding & Automation: Write production-quality, highly efficient, and scalable code primarily in Python for data processing, analysis, and model creation. Conduct A/B testing, hypothesis testing, and rigorous model validation, continually iterating and tuning algorithms to maximize performance, accuracy, and efficiency. product managers, engineers, business stakeholders) to define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences. Deployment & MLOps: Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time. Programming: Expert proficiency in Python and its core data science libraries: Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases & Querying: Proficiency in SQL for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases is a plus. Big Data/Cloud: Experience with big data tools ( Spark, Hadoop ) and cloud computing platforms ( AWS, Azure, or GCP ) for scalable ML workflows. Ability to create clear, compelling data visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI to communicate insights. Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field. ~[Number] years of professional experience as a Data Scientist or in a highly quantitative role. A strong passion for data and an inherent curiosity to explore, question, and challenge assumptions. Storytelling: The ability to translate complex statistical and ML outputs into simple, business-relevant narratives and recommendations.