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- Tasks: Develop and implement advanced data models and algorithms to solve complex business problems.
- Company: Join a global management consultancy leading in innovative data solutions.
- Benefits: Enjoy remote work flexibility and competitive salary up to £90K.
- Why this job: Be part of a dynamic team, leveraging cutting-edge technologies to drive impactful change.
- Qualifications: Master's or Ph.D. in relevant fields with 5+ years of Data Scientist experience required.
- Other info: Experience with Databricks, cloud platforms, and machine learning is essential.
The predicted salary is between 54000 - 126000 £ per year.
We are looking for a skilled Data Scientist for a Global Management consulting Client. We are seeking a Data Scientist with expertise in Databricks, SQL, cloud platforms, and machine learning to develop and implement advanced data models, algorithms, and solutions to complex business problems. This role requires proficiency in the Databricks ecosystem, as well as experience in working with large-scale data processing and cloud environments such as AWS, Azure, or Google Cloud.
Responsibilities:
- Should have at least 5 years of experience as a Data Scientist.
- Develop and implement data models and algorithms to solve complex business problems.
- Experience in machine learning models and algorithms using Databricks, Neo4j, Python, R, and big data technologies.
- Work with cloud platforms (AWS, Azure, Google Cloud) to design and implement data pipelines and storage solutions.
- Design and optimize SQL queries for large-scale data analysis.
- Utilize Databricks for data processing, analytics, and collaborating with team members to build scalable solutions.
- Leverage LLM (Large Language Models) for AI-driven projects, improving business processes and customer experiences.
- Collaborate with data engineers to build data pipelines and integrate various data sources.
- Analyze and interpret complex datasets to derive actionable insights and make data-driven recommendations.
- Develop clear and concise reports and visualizations to communicate findings to both technical and non-technical stakeholders.
- Stay current with emerging trends in machine learning, big data technologies, and cloud computing to continuously improve our solutions.
Qualifications:
- Master's or Ph.D. degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related fields.
- Proven experience in Databricks and its ecosystem (Spark, Delta Lake, MLflow, etc.).
- Strong proficiency in Python and R for data analysis, machine learning, and data visualization.
- In-depth knowledge of cloud platforms (AWS, Azure, Google Cloud) and related data services (e.g., S3, BigQuery, Redshift, Data Lakes).
- Expertise in SQL for querying large datasets and optimizing performance.
- Experience working with big data technologies such as Hadoop, Apache Spark, and other distributed computing frameworks.
- Solid understanding of machine learning algorithms, data preprocessing, model tuning, and evaluation.
- Experience in working with LLM (Large Language Models) and NLP (Natural Language Processing) tasks is a plus.
- Strong analytical and problem-solving skills with the ability to work independently and in a team environment.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred Skills:
- Experience with Databricks machine learning workflows and automation (e.g., MLflow).
- Familiarity with containerization technologies such as Docker and Kubernetes.
- Experience with version control tools (e.g., Git).
- Knowledge of data visualization tools like Tableau, Power BI, or matplotlib.
- Familiarity with DevOps practices in data science workflows.
Data Scientist employer: Careerwise
Contact Detail:
Careerwise Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your hands-on experience with Databricks and its ecosystem. Highlight specific projects where you've used Spark, Delta Lake, or MLflow, as this will demonstrate your practical knowledge and ability to apply these tools effectively.
✨Tip Number 2
Familiarise yourself with the latest trends in machine learning and big data technologies. Being able to discuss recent advancements or case studies during interviews can set you apart and show your passion for the field.
✨Tip Number 3
Network with professionals in the data science community, especially those who work with cloud platforms like AWS, Azure, or Google Cloud. Engaging in discussions or attending meetups can provide insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your experience with SQL and how you've optimised queries for large datasets. Be ready to share examples of how your analytical skills have led to actionable insights in previous roles.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, Neo4j, and cloud platforms like AWS, Azure, or Google Cloud. Use specific examples of projects where you've developed data models or implemented machine learning algorithms.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data science and how your skills align with the role. Mention your proficiency in Python and R, and provide examples of how you've used these languages to solve complex business problems.
Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or a brief description of these projects in your application. Highlight your experience with big data technologies and any machine learning workflows you've automated.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail during the interview process. Brush up on your knowledge of SQL, machine learning algorithms, and data visualisation tools, as well as your experience with LLM and NLP tasks.
How to prepare for a job interview at Careerwise
✨Showcase Your Technical Skills
Be prepared to discuss your expertise in Databricks, SQL, and cloud platforms. Highlight specific projects where you've successfully implemented data models or algorithms, and be ready to explain the technical details behind your work.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your analytical skills. Prepare examples of complex business problems you've solved using machine learning or big data technologies, and outline your thought process in tackling these challenges.
✨Communicate Clearly
Since you'll need to explain complex concepts to non-technical stakeholders, practice articulating your ideas clearly and concisely. Use visual aids or examples to help convey your points during the interview.
✨Stay Updated on Industry Trends
Research the latest trends in machine learning, big data, and cloud computing. Being knowledgeable about emerging technologies will not only impress your interviewers but also demonstrate your commitment to continuous learning in the field.
