At a Glance
- Tasks: Lead advanced analytics initiatives and design scalable models for actionable insights.
- Company: Innovative data science team in a collaborative environment.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement potential.
- Why this job: Make a real impact by transforming big data into meaningful insights.
- Qualifications: Experience in Python, machine learning, and data visualisation tools.
The predicted salary is between 63000 - 77000 £ per year.
Location: Creechurch, London - UK
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. We are in collaboration with leading academics, industry experts, and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
What you’ll achieve:
- As a Data Science Analyst, you will lead initiatives in advanced analytics, machine learning, and data-driven decision-making.
- You will design scalable models, optimize algorithms, and collaborate across teams to deliver actionable insights.
- You will champion innovation and ensure data science solutions align with business objectives.
- You’ll develop fundamental new approaches to generating meaning and value from internal data technologies, often working closely with business leaders and their supporting functions.
- You’ll develop new methodologies and tools to enable advanced modeling and statistical analysis against petabyte-scale data sets from disparate data sources.
- You’ll seek to understand our stakeholder’s most urgent questions and use statistical methods and models to provide answers or generate recommendations for process improvements.
- You will work with data engineers to create new tools and features that support sophisticated analytics within the database.
Key Accountabilities:
- Designs, develops and programs methods, processes and systems to consolidate and analyze unstructured data to generate actionable insights and solutions.
- Develops and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources.
- Constructs predictive models, algorithms and probability engines; verifies model and algorithm effectiveness based on actual results.
- Interacts with business leaders and team members to understand business strategy, conditions and problem areas.
- Contributes to business strategy and influences decision making based on information gained from deep dive analysis.
- Produces actionable & compelling recommendations by interpreting, exploring, identifying and communicating insights discovered from complex data sets.
- Partners with both internal & external sources to gather and examine data from disparate sources with the goal of discovering previously hidden insights.
Knowledge and Application:
- Learns to use industry standard data science and data engineer best practices.
- Applies knowledge and basic problem-solving techniques to define and resolve problems.
- Determines a course of action based on guidelines set forth by leadership and senior team members.
Problem Solving:
- Works on problems of limited scope.
- Follows standard practices and procedures in analyzing situations or data from which answers can be readily obtained.
- Work is reviewed periodically based on a set of defined procedures or precedence.
- Normally receives general instruction on work and new assignments.
Collaboration and Interaction:
- Interacts daily with subordinates and/or functional peer groups. Interaction normally involves exchange or presentation of factual information.
- Conveys straightforward information to audiences.
Technical/Additional Skills:
- Understanding of Python programming and other relevant languages (R, Java, SQL, DAX).
- Understanding of PowerAutomate or equivalent automation applications.
- Ability to use standard Data Visualization tools (PowerBI).
- Technical knowledge of machine learning and best practices.
- Computer Science or similar degree.
- Business case management and Business Analysis expertise.
- Excellent communication skills, with the ability to build long lasting relationships with key stakeholders.
Analyst, Data Science in London employer: Dell, Inc.
Dell Technologies is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of the United Kingdom. Employees benefit from comprehensive growth opportunities, including professional development programmes and access to cutting-edge resources, all while contributing to meaningful projects that shape the future of technology. With a commitment to ethical practices and a supportive environment, Dell ensures that every team member can thrive both personally and professionally.
StudySmarter Expert Advice🤫
We think this is how you could land Analyst, Data Science in London
✨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 Dell, Inc.!
✨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 Analyst, Data Science at Dell, Inc..
✨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 Dell, Inc..
✨Apply Directly through Our Website
When you find a suitable opening like Analyst, Data Science at Dell, Inc., 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 Analyst, Data Science in London
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 Dell, Inc., 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 Dell, Inc.. 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 Dell, Inc.
✨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 Dell, Inc.!
✨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.