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For Companies At a Glance
- Tasks: Collaborate with teams to deliver data-driven solutions and enhance reporting capabilities.
- Company: Join a leading client known for innovation in data analytics and AI.
- Benefits: Enjoy a hybrid work model with flexible remote options and modern tech tools.
- Why this job: Be part of a dynamic team driving impactful analytics in a fast-paced environment.
- Qualifications: Experience in predictive analytics, Power BI, Python, and a background in finance is preferred.
- Other info: Opportunity to work on cutting-edge projects with a focus on AI adoption.
The predicted salary is between 36000 - 60000 £ per year.
Our leading client is currently recruiting for talented Senior Analytics Engineer to join their Data Analytics team. You will play a pivotal role in advancing their reporting, predictive analytics & AI capabilities across the company. This is a hybrid role with 2 days in Manchester office per week.
About the Role:
In this business-facing position, you will collaborate closely with various teams to plan and coordinate the delivery of data-driven solutions that align with our business objectives. Our team boasts strong expertise in Power BI and Tabular models, and we are looking to enhance it further with your background in machine learning and AI. With our recently launched modern Data Platform featuring embedded Power BI, you will combine technical prowess with business insight to develop content through an AGILE delivery methodology.
Key Responsibilities:
- Partner with business teams to identify reporting needs and deliver effective solutions
- Develop and maintain reporting solutions using Power BI, SSAS Tabular, and predictive tools
- Lead technical development and provide guidance on analytics projects
- Enhance and maintain existing reporting assets
- Ensure thorough testing and proper documentation of solutions
- Optimize data models and promote best practices for performance
- Stay updated with data and reporting technology trends, including supporting AI adoption in 2025
Required Experience:
- Proven experience in predictive analytics, including forecasting and scenario modeling
- Advanced development skills in SSAS Tabular data models
- Expertise in Power BI, including dashboards and paginated reports
- Practical experience with AI tools to enhance analytics or operations
- Proficiency in Python coding
- Strong DAX and T-SQL skills, including query optimization
- Industry experience in insurance or financial services is a plus
- Familiarity with Databricks is advantageous
Analytics Consultant employer: Sanderson
Contact Detail:
Sanderson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Consultant
✨Tip Number 1
Familiarise yourself with the latest trends in predictive analytics and AI tools. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Network with professionals in the data analytics space, especially those who work with Power BI and SSAS Tabular models. Engaging in conversations on platforms like LinkedIn can help you gain insights and potentially get referrals.
✨Tip Number 3
Prepare to showcase your technical skills in Python, DAX, and T-SQL during the interview. Consider working on a small project or case study that highlights your ability to optimise queries and develop effective reporting solutions.
✨Tip Number 4
Research the company’s current data platform and any recent projects they’ve undertaken. This will not only help you understand their needs better but also allow you to tailor your responses to show how you can contribute to their goals.
We think you need these skills to ace Analytics Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with predictive analytics, Power BI, and SSAS Tabular models. Use specific examples that demonstrate your technical skills and how they align with the job requirements.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss your background in machine learning and AI, and how you can contribute to their data-driven solutions. Be sure to mention any relevant industry experience.
Showcase Relevant Projects: If you have worked on projects involving Python coding, DAX, or T-SQL, include these in your application. Briefly describe the challenges you faced and how you overcame them, particularly in relation to reporting and analytics.
Highlight Continuous Learning: Mention any recent courses or certifications related to data analytics, AI, or new technologies. This shows your commitment to staying updated with industry trends and your readiness to support AI adoption in 2025.
How to prepare for a job interview at Sanderson
✨Showcase Your Technical Skills
Make sure to highlight your experience with Power BI, SSAS Tabular, and any predictive analytics tools you've used. Be prepared to discuss specific projects where you applied these skills, as this will demonstrate your technical prowess.
✨Demonstrate Business Acumen
Since the role involves collaborating with various business teams, it's crucial to show that you understand how data-driven solutions can align with business objectives. Prepare examples of how your analytics work has positively impacted business outcomes in the past.
✨Prepare for Technical Questions
Expect questions related to Python coding, DAX, and T-SQL. Brush up on your query optimisation techniques and be ready to solve problems on the spot, as this will showcase your analytical thinking and problem-solving abilities.
✨Stay Updated on Industry Trends
Familiarise yourself with the latest trends in data analytics and AI, especially those relevant to the insurance or financial services sectors. Being knowledgeable about upcoming technologies will show your commitment to continuous learning and innovation.
