At a Glance
- Tasks: Lead data management activities for projects, ensuring quality and compliance.
- Company: Join a forward-thinking organisation dedicated to innovation in data management.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on continuous improvement and team development.
- Why this job: Make a real impact by managing critical data processes and leading project teams.
- Qualifications: Experience in data management and strong leadership skills required.
The predicted salary is between 59400 - 72600 £ per year.
Primary point of contact (POC) for internal and external stakeholders for DM related activities for assigned projects/studies.
Creates and executes project work plans and revises as appropriate to meet changing needs and requirements.
Overall responsible for DM activities for assigned projects from beginning to end including study start-up, study conduct and study close-out activities within agreed timeline, quality and cost.
Ensure quality and compliance with protocol, standard operating procedures (SOPs), ICH - GCP and applicable regulatory requirements for assigned projects.
Prepare/revise, review and/or approve project specific essential documents, plans, deliverables, etc.
Ensure data management trial master file (DMTMF) is established and updated on regular basis for assigned projects.
Perform manual review of data listings, quality control (QC) checks/reviews, SAE reconciliations on need basis.
Provide periodic progress/status reports/updates to function head – CDM/head of department (HOD), internal and external stakeholders for assigned projects.
Lead and participate in project specific meetings and teleconferences.
Develop new or revise existing DM SOPs.
Provide feedback for continuous improvement of SOPs from DM and other cross functional SOPs.
Provide support for external audits, certification audits and regulatory inspections from DM in consultation with HOD.
Conduct training for project team and/or DM team, on need basis.
Manage and assign resources and responsibilities for assigned projects.
Communicate project expectations/requirements/scope including any updates adequately to project team in a timely manner.
Assist HOD in interview and selection of new employees in the department/function, if required.
Proactively identify and communicate potential risks/challenges/issues to relevant stakeholders and take timely necessary actions.
Coach, mentor, motivate and supervise project team members and contractors, and influence them to take positive action and accountability for their assigned work.
Other responsibilities as delegated by the reporting manager/HOD or senior management.
Lead Data Manager in Manchester employer: Tech Observer
As a Lead Data Manager at our company, you will thrive in a dynamic and supportive work environment that prioritises employee growth and development. We offer comprehensive training programs, a collaborative culture, and the opportunity to lead impactful projects in a location known for its vibrant community and commitment to innovation. Join us to make a meaningful difference while enjoying competitive benefits and a strong work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Manager in Manchester
✨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 Tech Observer!
✨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 Lead Data Manager at Tech Observer.
✨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 Tech Observer.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Manager at Tech Observer, 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 Lead Data Manager in Manchester
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 Tech Observer, 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 Tech Observer. 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 Tech Observer
✨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 Tech Observer!
✨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.
