
Data Analyst Lead
2 days ago
About the Role
","This role is a critical member of our team, working closely with data scientists and product managers to deliver high-quality results. The ideal candidate will have a strong foundation in data analysis and be able to execute on projects and initiatives with minimal supervision.
","- Our team is responsible for delivering one or more data products, often through data science algorithms, and we are looking for someone who can support this work by diving into large datasets, performing large-scale data preparation, and reviewing precision and recall of data science algorithms at scale.
- The successful candidate will need to have a keen eye for detail, good analytical skills, and expertise in at least one data analysis system. Above all, they will need curiosity, dedication to high-quality work, and an interest in the world of scientific research.
- Because we work with a range of stakeholders around the world, we ask for candidates to demonstrate a high level of English proficiency.
Requirements
","- A minimum of 3 years of work experience in a related field
- Coding skills in at least one programming language (preferably Python) and SQL
- Familiarity with common string manipulation functions such as regular expressions (regex)
- Prior exposure to data analysis in a tabular form, for example with Pandas or Apache Spark/Databricks
- Knowledge of basic statistics relevant to data science eg. precision, recall, F-score
- Knowledge of visualization tools such as Tableau/Power BI is a plus
- Experience of working with Agile tools such as JIRA is a plus
Benefits
","- Build and maintain strong relationships with data scientists and product managers
- Align activities with data scientists and product managers
- Present achievements and project status updates, both written and verbally, to various stakeholders
Competencies
","- Collaborates well and works effectively as part of a team
- Takes initiative and is proactive in suggesting approaches or solutions to problems
- Drives for results by taking a task to a polished conclusion
Key Results
","- Understand the requirements of a given task
- Identify, gather, prepare and refine data
- Interpret and understand large data sets
- Report findings to stakeholders through effective storytelling
- Formulate recommendations and requirements
- Identify and address new opportunities
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