Data Scientist

Job Description

Data Scientist (Expertise in Databricks, Neo4j) - London - Remote Role - up to £90K - for a global management consultancy.

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 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 Models) and NLP (Natural 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.

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.