What is this Apprentice Program?
The LunarTech Data Science & Bioinformatics Apprentice Program is a structured, research-driven learning experience designed for aspiring data scientists who want to work at the intersection of AI, advanced analytics, and life sciences.
This program combines applied data science practice with structured education through LunarTech Academy, while contributing to real-world AI and data initiatives across LunarTech’s ecosystem. Apprentices may work on projects spanning healthcare analytics, bioinformatics pipelines, predictive modeling, industrial optimization, and AI-powered decision systems developed through LunarTech Labs.
You will collaborate with AI engineers, researchers, and product teams to design data pipelines, build predictive models, analyze complex datasets, and extract meaningful insights from high-dimensional data — including biological and biomedical datasets where applicable.
The program places strong emphasis on AI-driven data modeling, statistical rigor, experimental design, and interpretable machine learning systems, especially in domains where precision and reliability are critical, such as healthcare and bioinformatics.
This apprenticeship is designed to shape data scientists who combine mathematical depth, computational skill, and scientific thinking.
What You’ll Gain
- A LunarTech Academy Scholarship, providing structured daily education in AI, advanced statistics, and scientific computing
- Deep exposure to AI-driven analytics, predictive modeling, and data-centric system design
- Hands-on experience working with real-world structured and unstructured datasets
- Practical experience in healthcare and bioinformatics data workflows (where applicable)
- Direct mentorship from experienced AI engineers and data scientists
- Exposure to cross-industry data applications (healthcare, energy, construction, telecommunications, education)
- Experience designing reproducible experiments and evaluating model performance
- Development of technical presentation and scientific communication skills
- Structured feedback and research-style review cycles
- A portfolio of real-world data science and analytical projects
By the end of the program, you will understand how to design, evaluate, and deploy robust AI-driven analytical systems, with particular sensitivity to scientific and biomedical contexts when applicable.
Program Duration & Conditions
- Location: Armenia (Remote/Hybrid collaboration model)
- Duration: 6 or 12 months (depending on candidate background and experience level)
- Compensation: Unpaid apprenticeship
- Includes: LunarTech Academy Scholarship + structured mentorship
- Language Requirement: Minimum B1 English proficiency (international team across multiple nationalities and continents)
- Eligibility: Bachelor’s degree (completed or in progress) in Data Science, Computer Science, Bioinformatics, Statistics, Mathematics, or related field
This program is designed for analytically rigorous, research-oriented individuals who want to operate in an international, high-performance AI and data science environment.
Key Responsibilities
- Assist in building and validating predictive models and machine learning systems
- Design and implement data preprocessing and feature engineering pipelines
- Analyze large-scale structured and unstructured datasets
- Contribute to bioinformatics workflows (e.g., genomic, transcriptomic, or biomedical data analysis) where relevant
- Perform statistical testing, hypothesis validation, and model evaluation
- Develop reproducible notebooks, documentation, and experiment tracking workflows
- Collaborate with AI engineers and domain experts to translate insights into deployable solutions
- Apply structured AI insights and statistical reasoning to improve model interpretability and robustness
Required Skills & Qualifications
- Strong foundation in statistics, probability, and linear algebra
- Proficiency in Python (NumPy, Pandas, Scikit-learn, or similar libraries)
- Understanding of machine learning concepts and evaluation metrics
- Experience with data analysis through academic, research, or personal projects
- Familiarity with data visualization and exploratory data analysis
- For bioinformatics focus: foundational knowledge of genomics, biological data formats, or computational biology workflows is a plus
- Analytical mindset with strong attention to methodological rigor
- Ability to document findings clearly and present insights effectively
- Minimum B1 level English proficiency (required for international collaboration)
- Strong curiosity and disciplined research mindset
We are looking for data scientists who think scientifically, model rigorously, and are ready to build AI-powered analytical systems that drive evidence-based decisions across industries and life sciences.
