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For Companies At a Glance
- Tasks: Lead data-driven projects, manage timelines, and deliver actionable insights.
- Company: Join N Consulting Ltd, a dynamic firm focused on innovative data solutions.
- Benefits: Enjoy hybrid work, flexible hours, and opportunities for professional growth.
- Why this job: Make an impact with data while collaborating with diverse teams in a supportive culture.
- Qualifications: 3+ years in project management and data analytics; proficiency in SQL and Python required.
- Other info: PMP or Agile certifications are a plus but not mandatory.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a Project Manager with hands-on Data Analysis experience to lead and deliver data-driven projects. This role requires a unique blend of project management expertise and technical proficiency in data analytics. You will work closely with cross-functional teams to deliver actionable insights, ensuring projects meet business objectives and timelines.
Key Responsibilities:
- Project Management: Plan, execute, and monitor data analytics projects from inception to completion. Define project scope, objectives, timelines, deliverables, and resource requirements. Collaborate with stakeholders to gather requirements, align expectations, and ensure successful project delivery. Manage project risks, issues, and dependencies while ensuring quality and adherence to deadlines. Document project progress, deliver regular status reports, and facilitate communication across teams.
- Data Analytics: Perform hands-on data extraction, transformation, and analysis using SQL, Python, Excel, or other analytics tools. Interpret complex data sets to identify trends, patterns, and actionable insights. Design and maintain dashboards and reports using BI tools (e.g., Power BI, Tableau, or similar). Validate data quality, accuracy, and integrity throughout the analysis process. Support decision-making by providing analytical insights and data-driven recommendations.
Required Skills & Qualifications:
- Project Management: Proven experience (3+ years) managing data analytics or data-related projects. Strong understanding of project management methodologies (Agile, Scrum, Waterfall). Experience in stakeholder management and leading cross-functional teams.
- Data Analytics: Hands-on experience with SQL, Python, or other data analysis languages. Proficiency in data visualization tools (Power BI, Tableau, or similar). Strong analytical and problem-solving skills with the ability to translate business needs into technical requirements.
- General: Excellent communication and interpersonal skills. Ability to manage multiple projects simultaneously and prioritise effectively. Bachelor's degree in Data Science, Computer Science, Business, or a related field (or equivalent experience). PMP, PRINCE2, or Agile certifications (preferred but not required).
Program manager - Data Analyst employer: N Consulting Ltd
Contact Detail:
N Consulting Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Program manager - Data Analyst
✨Tip Number 1
Familiarise yourself with the specific project management methodologies mentioned in the job description, such as Agile and Scrum. Being able to discuss these frameworks confidently during your interview will demonstrate your understanding and readiness for the role.
✨Tip Number 2
Brush up on your data analysis skills, particularly in SQL and Python. Consider working on a small project or case study that showcases your ability to extract and analyse data, as this practical experience can be a great talking point in interviews.
✨Tip Number 3
Prepare examples of past projects where you successfully managed cross-functional teams. Highlight your role in stakeholder management and how you ensured project objectives were met, as this will illustrate your leadership capabilities.
✨Tip Number 4
Get comfortable with data visualisation tools like Power BI or Tableau. If you have the opportunity, create a sample dashboard that demonstrates your ability to present data insights clearly and effectively, which can impress potential employers.
We think you need these skills to ace Program manager - Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in project management and data analytics. Use keywords from the job description, such as 'SQL', 'Python', and 'data visualization tools' to catch the employer's attention.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analysis and project management. Mention specific projects you've managed and how your analytical skills have led to successful outcomes. This is your chance to stand out!
Showcase Relevant Skills: In your application, emphasise your hands-on experience with data extraction and analysis. Provide examples of how you've used tools like Power BI or Tableau to create dashboards or reports that influenced decision-making.
Highlight Certifications: If you have any relevant certifications like PMP, PRINCE2, or Agile, make sure to include them in your application. These can set you apart from other candidates and demonstrate your commitment to professional development.
How to prepare for a job interview at N Consulting Ltd
✨Showcase Your Project Management Skills
Be prepared to discuss your previous project management experiences in detail. Highlight specific projects where you successfully managed timelines, resources, and stakeholder expectations, especially in data analytics.
✨Demonstrate Technical Proficiency
Make sure to brush up on your technical skills, particularly in SQL, Python, and data visualisation tools like Power BI or Tableau. Be ready to provide examples of how you've used these tools to extract insights from data.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think of examples where you had to manage risks or resolve issues during a project, and be ready to explain your thought process.
✨Communicate Clearly and Effectively
Since excellent communication is key for this role, practice articulating your thoughts clearly. Be concise when explaining complex data concepts, and ensure you can translate technical jargon into business language.
