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Establish data governance practices for managing various types of data, including personally identifiable information, data quality, and validation standards. Hands-on experience working within an enterprise-scale Data Platform, while setting best practices for security, privacy, monitoring & alerting, and CI/CD (ideally with Google Cloud Platform, Airflow, Databricks, and Tableau.
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Manage all aspects of data products quality and integrity in partnership with compliance, governance, and technology teams. The Analytics & Data (A&D) team within Morgan Stanley Wealth Management Client Solutions Group owns all the management reporting, customer and product behavior insights, and predictive modeling in support of Wealth Management, Banking, and Firmwide Marketing.
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As a Marketing Data Scientist, you will play a critical role in accelerating Cash App’s growth by creating and improving how we measure the impact of all our marketing efforts. The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day.
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Utilize data visualization techniques to explain data and models to clients and internal teams (Power BI, Tableau, Looker, etc. The Semi Senior Data Scientist will help develop solutions for digital marketing use cases using statistical, data mining methods and data engineering solutions, working closely with our Analytics, Media Account Management, and Solutions Engineering teams.
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Job Description The Data Science team at Cash App derives valuable insights from our extremely unique datasets and turns those insights into actions that improve the experience for our customers every day.
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Leads core technical teams to control and enhance master data quality and standards. Establishes data quality metrics for master data. This distributed team will implement a defined process focused on data standards, data quality and enforcing the controls of the company’s most important data.
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Understanding of SaaS, iPaaS and Data platforms like Salesforce, NetSuite, Boomi, Apigee, Snowflake, Azure Data Platform etc. Certification in any enterprise architecture framework like TOGAF is good to have, or at least you should be able to understand all aspects of enterprise architecture including business architecture, data architecture, application architecture and infrastructure architecture.
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In this position you will be working closely with business and Digital leaders to develop and implement a corporate data strategy and data architecture, including the approach to data management, data governance and data quality management, all in alignment with our corporate strategy and enterprise architecture.
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Knowledge with technology application and infrastructure components such as Servers, Storage, Networking, Application Development, SDLC, End User Platforms, Digital Workflow, Artificial Intelligence & Machine Learning, Cloud technologies, Data Engineering, Mobile/Web, and Database Management systems.
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DE developing, designing, and implementing scalable and efficient data architectures, using data warehousing solutions including Amazon Redshift, Oracle, Snowflake, ETL (Extract, Transform, Load) processes; and performing data cleansing, blending, parsing and transformations using Alteryx; and conducting workflow automation and data integration using Informatica.
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Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and cloud data services (e.g., Redshift, BigQuery, Snowflake). Competence with BI tools for data analysis (Power BI, Tableau, Looker, etc.
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Experience building in, and potentially standing up, cloud-based data science environments (Posit Workbench, DataBricks, Sagemaker) Utilize modern, open-source data scientific workflows (SQL, R/Python, Github) to create highly accurate or explainable predictive/prescriptive models.
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Recruter et diriger une petite équipe de data scientists au fil de l'évolution des besoins de Nestlé. Connaissance d'Azure, Databricks, DBT, Snowflake, PowerBI est un plus. Master (les Grandes Écoles en sciences sont un plus) et/ou doctorat en STEM (très apprécié), de préférence avec une spécialisation en statistiques.
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Experience with machine learning technology, such as: big data stacked Java, Python, R, Scala and visualization techniques, including Dash, Tableau and Angular. Experience with both traditional SQL and modern NoSQL data stores including SQL, and large-scale distributed systems such as Hadoop and/or working in Snowflake/Databricks.
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Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using Apache suite (airflow, spark), SQL, Python, ETL, and AWS big data technologies.
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data quality jobs Title: developer Company: Capgemini Holding in Snowflake, AZ
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