Scientist, Data Science

What You Will Contribute To Altos

We have an opportunity available for a Data Scientist to work in the field of cells, genomics and related areas.

Responsibilities

• Generate insights and models from multi-omics datasets (using public and internal data) to understand patterns, trends and relationships within data to inform decision-making and solve problems.
• Design, develops and programs methods, processes, and systems to extract, consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights.
• Build databases and is responsible for the curation of Data, including experimental data management.
• Extracting knowledge, insights and predictions from data using statistical methods, machine learning and data visualization.
• Work with scientists to identify optimal ways to prepare, annotate, store and navigate their datasets, including data application design and improvement.
• Define and document best practices for capturing and entering experimental metadata, and educate scientists and collaborators about these standards.
• Build pipelines for quality control, processing and analysis of raw targeted and un-targeted datasets.
• Develops and codes software programs and leverages algorithms and methodologies being developed by the scientific community for use cases of relevance to Altos Labs.
• Stay current with and adopt emergent analytical methodologies, tools and applications to ensure fit-for-purpose and impactful approaches.
• Partner closely with the Lab scientists and researchers to identify opportunities for data and insight mining to accelerate research.
• Embed analyses and visualizations in automated reports.

Who You Are

Minimum Qualifications

• PhD in interdisciplinary quantitative science such as Biology, Chemistry, Computer Science, Physics, etc.
• Relevant work experience in either an academic or industry setting.
• Working knowledge of cell biology and experience in large scale data analysis and statistical modeling on datasets like RNA-seq, ATAC-seq, protein network, pathways, etc.
• Proven track record of completed scientific projects as evidenced by publications and preprints.
• Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation.
  Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI.
• Ability to generate high quality ideas and be self-driven to explore.
• Strong experience in programming and comfortable modifying existing code-base.
• Experience with Python, R data cleaning and data manipulation or other related scientific languages.
• Willing to work in a collaborative environment and share periodic updates across the company.

Preferred Qualifications

• Strong and demonstrable experience working in an AWS compute environment is a major advantage.
• Experience integrating prior knowledge from public databases (e.g., KEGG) into omics data analysis pipelines.

The salary range for Cambridge, UK:

Scientist I, Data Science: £64,600 – £87,400
Scientist II, Data Science: £76,000 – £105,600
Senior Scientist I, Data Science: £88,000 – £132,000
Exact compensation may vary based on skills, experience, and location.