Senior Data Analyst I

About the Role

As a Senior Data Analyst, you have a solid understanding of best practices and can execute projects and initiatives without supervision from others.You are able to create advanced-level insights and recommendations.You are able to lead analytics efforts with high complexity, mostly independently.

Responsibilities

• The Senior Data Analyst role will support data scientists working within the Domains of the Research Data Platform. Domains are functional units thatare responsible fordelivering one or more data products, often through data science algorithms. Supporting this work could lead to a wide range of different analytical activities.
• For example, you may be asked to dive into large datasets to answer questions from product owners or data scientists; you may need to perform large-scale data preparation (data prep) in order to test hypotheses or support prototypes; you may be asked to review the precision and recall of data science algorithms at scale and surface these as dashboard metrics.
• You will need to have a keen eye for detail, good analytical skills, andexpertisein at least one data analysis system.Above all, youwill need curiosity, dedication to high quality work, and an interest in the world of scientific research and the products that Elsevier creates to serve it.

• Because you will need to communicate with a range of stakeholders around the world, we ask for candidates todemonstratea high levelof English.

Requirements

• Minimum work experience of 5 years
• Coding skills in at least one programming language (preferably Python) and SQL
• Familiarity with common string manipulation functions or libraries such as regular expressions (regex)
• Prior exposure to data analysis in a tabular form, for example with Pandas or Apache Spark/Databricks
• Experience of using basic statistics relevant to data science such as precision, recall and statistical significance
• Knowledge of visualization tools such as Tableau/Power BI is a plus
• Experience of working with Agile tools such as JIRA is a plus

Stake Holder Management

• Build andmaintainstrong 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,prepareand refine data
• Interpret and understand large data sets
• Report findings to stakeholders through effective story telling
• Formulate recommendations and requirements
• Identifyand address new opportunities