Data Scientist & Analytics Innovation Manager
Wavre, Belgium
6 dagen geleden

The Data Scientist & Analytics Innovation Manager will be responsible to support the Project Management community with analytics and reporting initiatives, with a focus on project management, resource demand, allocation, and capacity.

Key responsibilities :

Query data from database systems to provide ad-hoc project and resourcing analyses, insights, and recommendations (cycle time analyses, attrition analyses, etc.

for various customers.

Apply analytics and business acumen to diagnose planning and resource issues, and data issues, and generate insights and recommendations to demonstrably influence business decisions and outcomes

Work with customers and R&D Tech to gather and validate reporting and analytics requirements.

Work with R&D Tech to design, develop, and deploy PowerBI dashboards and analytics reports for teams, functional lines, governance and senior leaders.

Leverage modern data visualization and analytics technologies to create dynamic business dashboards to effectively communicate and bring key insights to life for customers.

Recommends quality metrics and ensures quality metrics are documented and tracked.

Promote the use of high-quality data and support a culture of fact-based decision-making in GSK by building capabilities and provide guidance and training to the community in visualization and analytics tool usage.

Stay abreast of Business Intelligence products and tools as well as business strategies and direction. Identify and bring forward new reporting and analytics technologies and opportunities that will positively impact R&D operations from a business perspective.

Advises senior leaders and key stakeholders on how data and analytics play a critical role in business management and optimization.

Contribute to the establishment, & the roll-out of an Digital & Data Analytics strategy.

Identify through analytics the development projects with maximum impacts across the R&D organization identifies

Serve as a member of the Master Data Strategy and Analytics team, participating in strategy development, and providing guidance around tactical decisions.

Contribute to a group of up to 10 experts. According to his / her knowledge / experience, this role may encompasses advisory, guidance and coaching of other professionals to ensure their development

Why you?

We’d like you to be able to :

Demonstrate experience in manipulating data in a big data environment experience of hive, SQL, PowerBI, is a must.

Curate large multiparametric data sets, and deploy algorithms to extract information and derive insights.

Demonstrate expertise and experience in delivering solutions to production via Continous Integration / Continuous Delivery.

Design, develop and implement analytical solutions using a variety of commercial and open source tools (common tools include Python, R, TensorFlow).

Develop and embed automated processes for predictive model validation, deployment, and implementation.

Identify opportunities to apply Machine Learning and Artificial Intelligence to build, test, and validate predictive models.

Effectively explain technical concepts to senior managers / stakeholders who have no understanding of data science as a discipline.

Explore how to visualise data to business owners in a way that speaks to the questions’ they are trying to answer.

Use these data visualisations to postively influence decision making and challenge the way business owners traditionaly think.

It would be fantastic if you have :

A higher degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Computational Biology, Computational Chemistry or related quantitative field.

Deep experience of Extraction, Transformation and Load processes in a big data environment (hive, Impala, SQL).

Strong experience in building Continuous Integration / Continuous Delivery pipeline (Jenkins, Azure DevOps).

Some experience with Hadoop Clusters.

Expert understanding of a programming language such as Python or R.

Experience with at least one Deep Learning framework such as TensorFlow, Keras, or PyTorch.

Excellent verbal communication skills.

Ability to work autonomously and collaboratively as part of a team to both teach and learn every day.

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