Junior Data Analyst at Arcadis working on digital asset management services. Contributing to projects involving data handling and supporting multi - disciplinary teams in delivering results.
About the role
- Senior Data Analyst optimizing strategic decisions through analytics engineering. Leveraging advanced analytical techniques for data-driven insights in television and film.
Responsibilities
- Use your indepth knowledge of code efficiency, optimization and refinement to help streamline our complex statistical model products that predict future slate content engagement and lifetime value of new and existing subscribers
- Apply advanced analytical engineering techniques focusing on QA analysis, efficiency and code optimization and productionalization to large-scale, high-dimensional data models in order to inform global business decisions
- Streamline and enhance advanced analytics techniques (data mining, data visualization, statistical analysis, causal inference, regression, machine learning, time-series forecasting) to large-scale, high-dimensional data in order to support the inform global business decisions
- Support complex projects, workstreams, and new initiatives & capabilities. This includes scoping out the breadth & depth of a project, helping manage the time & resources available, adapting plans to meet evolving needs and operational challenges, and representing the product with business partners and executive leadership
- Effectively communicate actionable results through compelling data storytelling across the organization
- Design, build, and maintain scalable data pipelines that transform raw data into reliable, analytics-ready datasets
- Automate data workflows and operational processes using Python to improve reliability, reduce manual effort, and enable faster delivery of insights.
Requirements
- Bachelor’s degree in Data Science, Engineering, Mathematics, Statistics, Operations Research, Computer Science, Applied Economics or related quantitative field
- 5+ years of analytical and QA experience
- 5+ years of experience developing and making efficient and productionalized machine learning models and performing data analysis with Python and/or R
- 5+ years of experience querying cloud-hosted databases with SQL
- Experience with statistical analysis and machine learning techniques: time-series forecasting, causal inference, regression, decision trees, clustering, etc.
- Demonstrated ability to work independently and apply creativity in solving open-ended problems
- Outstanding data storytelling skills through verbal, written, and visual communication
- Familiarity with data exploration and data visualization tools such as Looker, Tableau, or JupyterLab/Notebook
- Ability to explain how models are used and how algorithms behave to both technical and non-technical audiences
- Experience working with modern data pipeline and orchestration tools such as dbt, Airflow, or similar technologies
- Experience engineering, deploying, and maintaining data solutions using technologies like Databricks, S3, and Spark
Benefits
- A bonus and/or long-term incentive units may be provided as part of the compensation package
- Full range of medical, financial and/or other benefits
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