At a Glance
- Tasks: Analyse massive datasets and develop innovative data models to drive insights.
- Company: Dynamic startup focused on data-driven decision making.
- Benefits: Top-notch equipment, health benefits, equity options, and generous paid time off.
- Other info: Collaborative environment with opportunities for personal growth and quarterly hack weeks.
- Why this job: Join a team where your data skills can make a real impact.
- Qualifications: Experience in data engineering, strong SQL skills, and a degree in a related field.
The predicted salary is between 54000 - 66000 £ per year.
Analyze our data (10TB) and help us answer data-driven questions.
Design, develop and deploy data models, algorithms, and tools to support data analysis and visualization.
Build and maintain a scalable data pipeline that collects, processes and stores data from various sources, ensuring data accuracy, reliability, and availability. Currently we’re based on DBT + Segment + Redshift.
Collaborate with software engineers, data scientists, and product managers to ensure data-driven decision making across the organization.
Perform exploratory data analysis and statistical modeling to identify insights and trends that drive product and business decisions.
Develop and implement data quality and data governance standards to ensure data accuracy and consistency.
Work with stakeholders to understand their data needs and translate them into technical requirements.
Stay up-to-date with the latest technologies, trends, and best practices in data engineering, data science, and analytics, and recommend new solutions and approaches that can benefit the company.
Benefits
- Great equipment: New laptop, monitor, and stipend for desk accessories.
- 401(k) Plan: Helping you save for the future.
- Equity: Employee-friendly equity terms.
- Health benefits: Top-tier health, dental, and vision insurance.
- Paid meals: Company-paid lunch, dinner, and coffee during workdays.
- Commuter benefits: Covering your commute costs.
- Paid time off: Four weeks of paid time off.
- Family leave: Sixteen weeks of parental leave.
- Quarterly hack weeks: Take time to develop what you feel most passionately about.
Qualifications
- Experience with cloud platforms such as AWS, GCP, or Azure, and their respective data services (e.g., S3, Redshift, BigQuery).
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
- Strong problem-solving and analytical skills, with experience in statistical modeling.
- Strong programming skills in SQL.
- Excellent communication skills and ability to work collaboratively with cross-functional teams.
- Self-starter with the ability to work independently in a fast-paced startup environment.
- Experience with data visualization tools such as Tableau, Looker, or Power BI.
- At least 4 years of experience in data engineering, with a focus on building scalable data pipelines and data models.
Data Scientist employer: Graphite
Graphite is an exceptional employer that fosters a culture of autonomy and collaboration, allowing Account Managers to thrive in a fully remote environment. With a strong emphasis on employee growth, flexible work arrangements, and competitive compensation, we empower our team members to produce their best work while enjoying the freedom to balance their personal and professional lives. Join us to be part of a mission-driven company that values impact and innovation in the digital marketing space.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨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 Graphite!
✨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 Graphite.
✨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 Graphite.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Graphite, 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
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 Graphite, 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 Graphite. 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 Graphite
✨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 Graphite!
✨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.
