Position Title:  Scientist Innovation and Program Statistics

We are looking for a Scientist – Innovation and Program Statistics to join our R&D team in Armenia.
This role bridges technical analysis, process design, and collaborative development. As part of a dynamic team, you will play a key role in statistical modeling, tool development, and process optimization to support multiple scientific and operational initiatives.

Key Responsibilities

• Conduct advanced statistical analyses on experimental and operational datasets, interpret results, and effectively communicate findings to scientists, engineers, and subject matter experts to drive data-based decision-making.

• Leverage statistical software and programming tools to conduct data analysis, generate reports, and develop interactive applications that support automation and improve analytical workflows.

• Design and analyze experiments (DoE) to support product development, process optimization, and scientific decision-making.

• Contribute statistical expertise to stability and shelf-life studies to ensure robust evaluation of product performance over time.

• Collaborate across cross-functional teams, attending and contributing to meetings to ensure effective communication, alignment, and progress on statistical initiatives.

Qualifications and Experience

• Education: Master’s degree in Industrial Engineering and Systems Management or a related quantitative field.

• Professional Experience: Proven track record in statistical analysis, data science, and research, ideally gained through roles in both corporate and academic environments. Previous experience includes positions as Statistician, Data Scientist, AI Researcher, and Scientist Statistician, with responsibilities spanning statistical modeling, data analysis, experiment design, and process optimization.

• Technical Skills: Proficiency in statistical software and programming tools, including R, Markdown, Quarto, Shiny, Python, and SQL. Strong ability to translate complex data into actionable insights and support decision-making across scientific and operational teams.