Junior AI Analyst – Entry-Level Data & Machine Learning Role

Looking for your first break in artificial intelligence? As a Junior AI Analyst you’ll dive into AI performance analysis, data processing, and model testing while sharpening Python and visualization skills. This entry-level AI position blends analytics, machine learning, and storytelling to accelerate your tech career… fast.

About the Team

A multidisciplinary, product-centric organization leverages cloud-native platforms to transform data into decision-ready insights. You’ll collaborate with seasoned data scientists, software engineers, and product owners who mentor, challenge, and celebrate your growth.

What You’ll Do

– Scrutinize AI system metrics, uncover anomalies, and report actionable findings.  

– Clean, transform, and validate structured and unstructured datasets using Python (Pandas, NumPy).  

– Execute controlled experiments, track model drift, and benchmark algorithms against baselines.  

– Create compelling dashboards in Tableau or Power BI to illustrate trends for technical and non-technical stakeholders.  

– Debug minor code issues, write unit tests, and automate routine checks with GitHub Actions.  

– Document methodologies and maintain a knowledge base for reproducibility.  

– Partner with data engineering to optimize data pipelines (Snowflake, BigQuery).  

– Present weekly “lightning talks” on emerging ML techniques—keep the team curious.  

– Continuously refine processes, suggesting improvements that boost speed and accuracy.  

– Embrace agile ceremonies, contribute to sprint planning, and estimate tasks with your squad.

Skills & Qualifications

– Bachelor’s degree in Computer Science, Data Science, Statistics, or related field (recent grads welcome).  

– 0-2 years of hands-on experience with Python for analysis or academic ML projects.  

– Foundational understanding of supervised, unsupervised, and reinforcement learning concepts.  

– Proficiency in SQL; exposure to cloud databases is advantageous.  

– Familiarity with data visualization libraries (Matplotlib, Seaborn) and BI tools (Tableau, Looker).  

– Solid grasp of statistical testing, confidence intervals, and significance levels.  

– Comfortable using Git, Jupyter Lab, and CLI environments.  

– Clear written and verbal communication—you translate numbers into narratives.  

– Adaptable, inquisitive mindset; you iterate quickly when priorities shift.  

– Work authorization in the United States.

Tech Stack You’ll Touch

Python 3.12, Scikit-learn, TensorFlow, PyTorch, Docker, Kubernetes, Snowflake, BigQuery, Airflow, Tableau, Power BI, GitHub Actions, RESTful APIs.

Why This Role Rocks

– Remote-first culture across US time zones—flex hours, zero commute.  

– Dedicated learning budget for Coursera, O’Reilly, or conferences.  

– Mentorship circles tailored to early-career technologists.  

– Impact: your analyses guide product upgrades used by millions.  

– Clear promotion pathway toward Data Scientist or ML Engineer tracks.

Culture Snapshot

Expect psychological safety, radical candor, and a bias for experimentation. We value diversity of thought, evidence-based decisions, and intellectual humility.

Application Note

Submit a concise résumé and a one-page case study or GitHub link demonstrating an AI-related project. Portfolios showcasing visualization work earn bonus points. No cover letter required—your work will speak.