At a Glance
- Tasks: Lead data excellence initiatives and collaborate with cross-functional teams to enhance data quality.
- Company: Join a leading global biopharmaceutical company focused on improving patient outcomes.
- Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
- Other info: Work in a collaborative culture that values innovation and continuous improvement.
- Why this job: Make a real impact by driving data-driven decision-making in a dynamic environment.
- Qualifications: 5+ years in data or analytics, strong communication skills, and technical expertise in SQL and Python.
The predicted salary is between 10000 - 96360 £ per year.
As a Data Excellence Lead you will be working in close collaboration with cross-functional partners in the UK & Ireland, IBU, ICC/GCC and global DD&T teams. You will lead the UK & Ireland data excellence agenda and partner with teams across Commercial, Access, Medical, Finance and DD&T to strengthen data foundations, improve data quality, scale adoption of data products, and enable better business decision-making. You will act as a business-facing DD&T partner for the UK & Ireland, ensuring global capabilities are deployed, adopted, and optimized to support customer engagement objectives and measurable business outcomes.
You will partner with cross-functional teams, including Commercial, Access, Medical and Finance, to define and manage the UK & Ireland data excellence roadmap and co-create deliverables with IBU DD&T. You will lead and implement data integration and EDB ingestion priorities for the UK & Ireland, ensuring data is fit for use, consumable by analytics and product teams, and connected to clear business needs. You will act as a data ambassador, partnering with cross-functional teams to raise data and technology fluency across the UK & Ireland and build a stronger data-driven culture.
Job Responsibilities
- Lead & implement data stewardship for the UK & Ireland. Set the stewardship approach with data owners and stewards, lead dataset reviews and issue prioritization, and ensure critical datasets have clear definitions, ownership, quality expectations, and usage guidance.
- Partner with IBU DD&T. Co-create data standards, data quality KPIs, tools and technologies, ensuring UK & Ireland priorities are reflected and aligned with broader DD&T direction.
- Embed global data standards locally. Lead the local application of data standards, align local field names and values to global definitions, maintain mapping tables, and manage exceptions so local data remains interoperable with global products.
- Partner with ICC/GCC for scalable delivery. Define outcomes, clarify delivery expectations, remove blockers, and ensure DD&T products and services are delivered with quality, adoption, and business value in mind.
- Lead & implement data quality management and remediation cycles. Execute recurring data quality monitoring, prioritize issues based on business impact, partner with source system SMEs on root causes, and ensure fixes are implemented through rules, transformations, process changes, or data corrections.
- Drive data documentation that makes data usable. Ensure data dictionaries, dataset descriptions, lineage notes, refresh frequency, business rules, and usage guidance are available, maintained, and practical for analysts, product teams, and business users.
- Lead & implement data integration and ingestion activities. Drive onboarding of data sources into EDB by aligning source profiling, extraction requirements, transformation logic, validation rules, and publishing steps with business needs and platform requirements.
- Own the UK & Ireland data roadmap and backlog. Maintain and prioritize the backlog across integrations, data fixes, governance activities, and capability improvements, and provide clear progress updates, risks, dependencies, and decisions needed to UK & Ireland stakeholders.
- Lead data fluency and adoption across the UK & Ireland. Partner with cross-functional teams to deliver practical enablement through training, office hours, playbooks, and reusable examples that improve how teams request, interpret, and use data.
What you bring to Takeda
- 5+ years of experience in data, analytics, digital, commercial excellence, or related disciplines, including experience leading cross-functional initiatives.
- Strong understanding of Takeda technology, data ecosystem, data architecture, governance, and analytics operating models.
- Preferred UK & Ireland, regional, or global experience, with strong understanding of how local teams operate and how enterprise capabilities are adopted in-market.
- Excellent ability to translate between technical and non-technical language, including presenting complex data topics to business stakeholders.
- Knowledge of Takeda MarTech and Salesforce tech stack and data modelling.
- Expert knowledge of SQL, R, Python.
- Hands-on working knowledge of Databricks, Power BI and data modelling.
- Knowledge of ETL, APIs and how to connect to databases.
- Technical knowledge of different digital channels including web, apps, surveys.
- Demonstrated project, program, stakeholder, and change management experience, including leading adoption of new capabilities across functions.
- Knowledge, experience and know-how of all data sources (customer, financial, patients, etc.) and underlying data structures.
- Knowledge of data privacy and compliance requirements in a regulated environment, including UK GDPR and the ABPI Code of Practice.
- Leads through influence, gaining support across teams and functions to move ideas from alignment to implementation.
- Works effectively in ambiguity, structures complex topics, manages trade-offs, and drives progress in new situations.
- Builds a collaborative network of relationships across functions and roles, and leverages formal and informal networks to accomplish goals.
- Communicates clearly and persuasively, translating data, technology, governance, and business needs into practical decisions and actions.
- Leads cross-functional teams to define, prioritize, and implement data-enabled growth initiatives.
- Extensive expertise, passion and understanding of data sources, especially the Customer Data domain within Takeda.
- Has knowledge, understanding and passion for Agile ways of working and the capability to lead by example.
Locations
Paddington, Great Britain
Base Salary Range: £70,100.00 - £96,360.00
For information about our benefits, please click here.
Worker Type: Employee
Worker Sub-Type: Regular
Time Type: Full time
StudySmarter Expert Advice🤫
We think this is how you could land Data Excellence Lead in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Takeda!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Excellence Lead at Takeda.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Takeda.
✨Apply Directly through Our Website
When you find a suitable opening like Data Excellence Lead at Takeda, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Excellence Lead in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Takeda, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Takeda. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Takeda
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Takeda!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
