Enterprise Data & Analytics Hunter β€” Hybrid London in Bristol

Enterprise Data & Analytics Hunter β€” Hybrid London in Bristol

Bristol Full-Time Home office (partial)
Snap Analytics

At a Glance

  • Tasks: Lead Data & Analytics sales engagements with top-tier clients using SAP, Snowflake, and Databricks.
  • Company: Snap Analytics, a dynamic company at the forefront of data solutions.
  • Benefits: Competitive base salary, uncapped commission, and hybrid work flexibility.
  • Other info: Exciting opportunity for career growth in a supportive team atmosphere.
  • Why this job: Join a fast-paced environment and drive impactful data solutions for leading enterprises.
  • Qualifications: Proven sales experience in data analytics and strong communication skills.

Snap Analytics in Bristol is seeking an Enterprise Account Executive to lead Data & Analytics engagements, focusing on SAP, Snowflake and Databricks.

You will own the full sales cycle from initial conversations to signed SOWs, supported by a BDR and a strong partner ecosystem.

The role is hybrid with London-based client activity; base salary Β£120,000 plus uncapped commission, with realistic OTE Β£180,000–£220,000.

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Enterprise Data & Analytics Hunter β€” Hybrid London in Bristol employer: Snap Analytics

At Snap Analytics, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. As a Senior AI Consultant in Bristol, you will not only have the opportunity to lead cutting-edge AI projects but also benefit from continuous professional development and a supportive team environment. Our commitment to employee growth, coupled with the vibrant city of Bristol, makes us an exceptional employer for those seeking meaningful and rewarding careers in AI.

Snap Analytics

Contact Details:

Snap Analytics Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Enterprise Data & Analytics Hunter β€” Hybrid London in Bristol

✨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 Snap Analytics!

✨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 Enterprise Data & Analytics Hunter β€” Hybrid London at Snap Analytics.

✨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 Snap Analytics.

✨Apply Directly through Our Website

When you find a suitable opening like Enterprise Data & Analytics Hunter β€” Hybrid London at Snap Analytics, 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 Enterprise Data & Analytics Hunter β€” Hybrid London in Bristol

Sales Cycle Management
Data & Analytics Expertise
SAP
Snowflake
Databricks
Client Engagement
Business Development Representative (BDR) Collaboration

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 Snap Analytics, 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 Snap Analytics. 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 Snap Analytics

✨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 Snap Analytics!

✨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.