Data Analyst

Alta Resource Technologies•Boulder, CO

3d•Onsite

About The Position

Alta Resource Technologies (Alta) is a next generation mining company that uses synthetic biology to separate critical minerals from conventional and unconventional resources, including e-waste. Founded in 2023, the company is expanding its team in Boulder, CO. The exponential growth of new tech industries, as well as the information technology sector, are driving historic growth in mineral demand and stressing existing supply streams. Meeting new demand, diversifying the supply chain, and producing minerals in a more sustainable manner requires the rapid development, deployment and scaling of new technologies. This mineral challenge represents a historic opportunity for technology development and value creation. Alta is proud to be at the vanguard of this mega trend. Role Summary We are seeking a Data Analyst with experience handling diverse scientific datasets. The person in this position will be tasked with performing ad hoc analysis and developing pipelines to securely store raw data, catalog this data and prepare it for downstream analysis. A successful candidate will establish real time monitoring of laboratory systems and accelerate product development by facilitating data integrity and real time analysis and dashboards for a variety of data types. This position will report to the VP Data and Information Systems.

Requirements

Bachelor's or Master's in Statistics, Biostatistics, Chemical Engineering, Bioinformatics, Cheminformatics, or related fields with 5-8 years of experience, or a PhD with 3-5 years of experience.
Strong grounding in frequentist statistics (DOE, ANOVA, regression); familiarity with Bayesian methods a plus.
Understanding and experience with Design of Experiment (DOE) approaches.
Proficiency with Python.
Proficiency with workflow management tools such as Nextflow or Snakemake.
Understanding of version control and experience with version control systems such as git.
Experience with dashboard development tools such as Dash or Streamlit.
Applicants must be authorized to work for ANY employer in the U.S.

Nice To Haves

Experience with process engineering.
Experience with common cloud providers (AWS/Azure).
Experience analyzing spectroscopy and spectrometry data.
Experience with common biological assays, including fluorometric assays, protein quantification, or gel electrophoresis.
Experience with shell scripting (Bash, Zsh, etc).
Experience with FAIR data principles.

Responsibilities

Collaborate with technical teams to ensure statistical rigor by supporting randomized experimental design and evaluating assay performance through power analysis.
Perform ad hoc statistical analysis on novel experiments, applying frequentist methods (ANOVA, regression, GLM) as the standard approach, with Bayesian methods where appropriate (e.g., small samples, sequential designs, incorporating prior data).
Develop standard analysis pipelines to ensure rigorous, reproducible results as projects advance.
Develop dashboards that allow key stakeholders to monitor processes and results in real time.
Develop processes to ensure data management is integrated with other support systems (LIMS, JIRA, etc)
Partner with technical and project leads across process engineering, chemistry, biology, and biotech to ensure data and data reports are available to the appropriate stakeholders.
Ensure all data packages and pipelines are documented and tested.