Data Analyst-Entry Level

Position Overview

Emonics LLC is seeking an enthusiastic and motivated Entry-Level Machine Learning Engineer to join our growing data science team in Dallas, TX. The ideal candidate will have a foundational understanding of machine learning concepts, data analysis, and software development practices, with a strong desire to learn and grow within a dynamic and collaborative environment.

Key Responsibilities

Assist in developing, training, and deploying machine learning models and algorithms.

Collaborate with data scientists and software engineers to collect, clean, and preprocess large datasets.

Support the design and implementation of scalable data pipelines and ML workflows.

Conduct model performance testing and optimize algorithms for accuracy and efficiency.

Participate in code reviews, documentation, and version control practices.

Stay up to date with emerging trends and tools in AI, ML, and data engineering.

Required Qualifications

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Basic knowledge of machine learning concepts (supervised, unsupervised learning, etc.).

Proficiency in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, or PyTorch.

Understanding of data manipulation and analysis using Pandas, NumPy, or SQL.

Strong analytical, problem-solving, and communication skills.

Eagerness to learn new technologies and contribute to a team environment.

Preferred Qualifications

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

Experience with version control systems (Git/GitHub).

Knowledge of data visualization tools (Matplotlib, Seaborn, or Power BI).

Internship or project experience in data science or machine learning.

What We Offer

Competitive entry-level salary and comprehensive benefits package.

Professional development and mentorship opportunities.

Collaborative and innovative work environment.

Opportunities to work on real-world AI and ML projects that make an impact.

How to Apply

Interested candidates can apply by submitting their resume and a brief cover letter highlighting relevant coursework, projects, or experience to: