Data Scientist

Cloud Bridge; Greater London; On-site; GBP 50,000 - 90,000; Full time

Job description

We are looking for an experienced Data Scientist to join our analytics team. The Data Scientist will be responsible for designing and implementing advanced data models, conducting statistical analysis, and leveraging machine learning algorithms to extract insights from large datasets. You will work closely with cross-functional teams to translate business problems into data science solutions that add value and inform strategic decisions.

Key Responsibilities:

• Use statistical analysis, machine learning, and data mining techniques to develop models that predict trends, classify data, and identify patterns from large datasets.
• Clean and preprocess data for analysis by handling missing values, outliers, and feature engineering.
• Implement machine learning algorithms (e.g., regression, classification, clustering, deep learning) to solve business problems and improve decision-making.
• Work closely with business leaders and cross-functional teams to understand business needs and translate them into data-driven solutions.
• Create insightful visualizations and dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to communicate findings effectively to non-technical stakeholders.
• Continuously evaluate and improve the performance of models through cross-validation, hyperparameter tuning, and other techniques.
• Stay up to date with the latest data science techniques, research, and tools, bringing innovative ideas to improve processes and methodologies.
• Work on automating processes for data collection, analysis, and model deployment to production using tools like Python, Flask, Docker, or Kubernetes.
• Document methodologies, processes, and insights, ensuring that they are understandable and actionable for business teams and stakeholders.

Required Skills & Experience:

• Strong understanding of statistical analysis and modeling techniques, including linear regression, time series, decision trees, and clustering algorithms.
• Proficient in machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras) for building and deploying predictive models.
• Proficient in Python, R, or similar programming languages for data analysis and machine learning.
• Experience with data manipulation and transformation tools such as Pandas, NumPy, and SQL for working with large datasets.
• Expertise in creating impactful visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI.
• Familiarity with big data tools and platforms like Hadoop, Spark, or cloud-based tools (e.g., AWS, Google Cloud, Azure).
• Strong analytical skills with the ability to identify, define, and solve complex business problems using data-driven methods.
• Excellent communication skills to present complex data science concepts to both technical and non-technical stakeholders.
• Experience with version control systems like Git for collaboration and code management.

Preferred Qualifications:

• AWS Certified Machine Learning – Specialty, Google Professional Data Engineer, or other relevant certifications.
• Master's or Ph.D. in Computer Science, Mathematics, Statistics, Engineering, or related field.
• Experience in deep learning frameworks like TensorFlow, Keras, or PyTorch for developing complex neural networks.
• Experience working with NLP techniques for text analysis and sentiment analysis.
• Familiarity with cloud platforms (AWS, GCP, Azure) and data engineering pipelines.
• Strong understanding of business operations and the ability to translate business challenges into actionable data science problems.

If you are an experienced Data Scientist with a passion for using data to drive business decisions and solve complex problems, we would love to hear from you!

#CBTR