Senior Strategic Data Services Account Manager

Senior Strategic Data Services Account Manager

Full-Time 50000 - 70000 £ / year (est.) No working from home possible
Hometrack

At a Glance

  • Tasks: Manage client accounts and drive success through data-driven insights.
  • Company: Hometrack, a leader in Data Services with a focus on customer success.
  • Benefits: Competitive salary, career growth, and cross-functional collaboration.
  • Other info: Dynamic London-based role with opportunities for professional development.
  • Why this job: Engage with senior decision makers and make a real impact in the industry.
  • Qualifications: Experience in account management and strong relationship-building skills.

The predicted salary is between 50000 - 70000 £ per year.

Hometrack is seeking an experienced Account Manager for its Data Services division.

You will own a portfolio of client accounts, managing onboarding through to renewal and upsell, while collaborating with product and delivery teams to secure customer success.

You will engage with senior decision makers, implement account plans, and drive value through data-driven insights and strong stakeholder relationships.

London-based role with cross-functional exposure.

#J-18808-Ljbffr

Senior Strategic Data Services Account Manager employer: Hometrack

Hometrack is an exceptional employer that champions innovation and collaboration in the financial services sector. With a strong focus on employee well-being, we offer flexible working arrangements, generous leave policies, and comprehensive benefits, including enhanced paternity leave and financial support for fertility treatments. Our vibrant work culture fosters professional growth through continuous learning opportunities, making it an ideal environment for Senior Machine Learning Engineers to thrive and contribute to meaningful projects.

Hometrack

Contact Details:

Hometrack Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Strategic Data Services Account Manager

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 Hometrack!

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 Senior Strategic Data Services Account Manager at Hometrack.

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 Hometrack.

Apply Directly through Our Website

When you find a suitable opening like Senior Strategic Data Services Account Manager at Hometrack, 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 Senior Strategic Data Services Account Manager

Account Management
Client Onboarding
Renewal Management
Upselling
Collaboration
Customer Success
Stakeholder Engagement

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 Hometrack, 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 Hometrack. 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 Hometrack

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 Hometrack!

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.