At a Glance
- Tasks: Transform business challenges into data-driven solutions using AI and machine learning.
- Company: Join EverQuote, a leader in AI-powered growth solutions for the insurance industry.
- Benefits: Competitive salary, equity options, health benefits, and a supportive work environment.
- Other info: Hybrid work model with opportunities for career growth and continuous learning.
- Why this job: Make a real impact in a fast-paced, innovative team while developing your data science skills.
- Qualifications: Bachelor's degree in a technical field and 2+ years of data science experience.
The predicted salary is between 63000 - 77000 £ per year.
Location: Belfast, NI / Hybrid (This role requires working in-office 3 days per week.)
About us: EverQuote is a leading AI-powered growth solutions partner for regulated property and casualty insurance entities, enabling the largest insurance carriers and thousands of agents to maximize customer acquisition across digital channels. Fueled by our proprietary data assets and our AI traffic engine, EverQuote is transforming the way providers attract and engage consumers to grow market share. Joining our team puts you at the forefront of this transformation. You will collaborate with a group of builders to solve complex problems and reshape a massive industry. If you want to drive real-world impact and do the best work of your career, you’ve found your home. We move fast, follow the data, and hold ourselves to high standards. If that's how you work too, this is the role for you.
About the role: EverQuote is seeking a Data Scientist to join our growing team! As a member of the Data Science team, you will be instrumental in delivering and deploying artificial intelligence and machine learning models that drive Everquote’s long term success.
What you’ll do:
- Work with a cross-functional team to convert business problems into scalable solutions using your knowledge of mathematics, statistics, and machine learning.
- You will join a team of talented and collaborative data scientists and machine learning engineers, and have the opportunity to establish yourself as a technical contributor as our team continues to grow.
What you bring to the team:
- Bachelor's degree in a technical field such as mathematics, statistics, computer science, or economics, or equivalent practical experience; a Master's degree or PhD in a relevant field is a plus.
- 2+ years of professional experience as a data scientist developing predictive models, preferably with experience deploying those solutions to production environments.
- Demonstrated success turning business problems into data problems and developing innovative solutions.
- Ability to explain results to technical and non-technical teammates, using strong communication and data visualization skills.
- Demonstrated experience building machine learning models using standard tools such as scikit-learn or R, to drive business improvements.
- Solid knowledge of applied mathematics and statistics and their common applications in online businesses.
Nice to have:
- Experience with, or strong interest in, understanding and optimizing online auctions for both bidders and sellers.
- Experience with, or strong interest in, optimization using reinforcement learning and contextual multi-armed bandits.
- Strong skills in statistical and scientific programming in Python or R, fluency in SQL, and proficiency with Jupyter notebooks.
- Experience packaging code for deployment and reusability.
- Enjoy sharing knowledge and mentoring teammates, and communicating designs to technical and non-technical stakeholders.
- An interest in staying current with data science trends and helping the team expand its tech stack.
- Comfortable working in an Agile team environment with everyday impact.
The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location. In addition to base salary, our total compensation package may include participation in variable cash bonus programs, equity, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility which are designated by role. Your recruiter can provide more details about the specific salary/OTE range for your role during the hiring process.
Statement on Fair Employment and Equal Opportunities: EverQuote NI is committed to ensuring equal opportunity for all job applicants and employees. We will not discriminate on the grounds of religious belief, political opinion, race, gender (including gender reassignment), sexual orientation, marital or civil partnership status, pregnancy or maternity, age, or disability. As a registered employer in Northern Ireland, EverQuote NI complies with the Fair Employment and Treatment (Northern Ireland) Order 1998. As part of the application process, you will be asked to complete a fair employment monitoring form; this information is used solely for monitoring purposes and does not form part of the shortlisting or selection decision. EverQuote NI carries out background checks on all candidates offered a position. A criminal record will not automatically disqualify you from working with EverQuote NI Limited; each case is considered on its individual merits in line with our fair recruitment practices.
Reasonable Adjustments: We are committed to ensuring an inclusive and accessible recruitment process for all candidates. If you require any reasonable adjustments or accommodations at any stage of the interview process, please let us know and we will work with you to arrange them.
For more information, visit EverQuote Investors and follow on LinkedIn.
Data Scientist in Belfast employer: EverQuote
EverQuote NI is an exceptional employer, offering a dynamic work culture that prioritises flexibility and work/life balance in the vibrant city of Belfast. With a strong focus on employee growth, we provide unparalleled learning opportunities, competitive salaries, and comprehensive benefits, including private healthcare and enhanced parental leave, making it an ideal place for passionate professionals to thrive and make a meaningful impact in the security software engineering field.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Belfast
✨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 EverQuote!
✨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 Data Scientist at EverQuote.
✨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 EverQuote.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at EverQuote, 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 Data Scientist in Belfast
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 EverQuote, 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 EverQuote. 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 EverQuote
✨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 EverQuote!
✨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.