We are seeking a highly skilled Senior Data Scientist to join our team and drive advanced data analytics, machine learning initiatives, and data-driven decision-making processes. The ideal candidate will have extensive experience in Python programming, with additional expertise in cloud platforms such as AWS or Azure being advantageous. Familiarity with Generative AI (Gen AI) concepts will be a significant asset as we continue to explore cutting-edge technologies for business solutions.
Key Responsibilities:
Lead the development and implementation of data science models, including machine learning, deep learning, and statistical models to address business challenges.
Design, develop, and optimise end-to-end data pipelines to extract, transform, and load data for analysis.
Collaborate with cross-functional teams to identify and deliver impactful data insights that influence business decisions.
Apply advanced machine learning techniques, including natural language processing, predictive modelling, and optimisation.
Stay abreast of the latest developments in Generative AI and evaluate its potential applications within the organisation.
Mentor junior data scientists and data engineers, providing guidance on best practices and model development.
Work with large datasets to build predictive models and perform data-driven decision-making.
Deploy and manage machine learning models in production environments on cloud platforms (AWS or Azure).
Collaborate with stakeholders to define project objectives, scope, and deliverables.
Required Skills and Qualifications:
Bachelor's or Master's degree in Data Science, Mathematics, Computer Science, Statistics, or a related field.
5+ years of experience in data science, machine learning, or a related role.
Proficiency in Python for data analysis, machine learning, and statistical modelling.
Experience with cloud technologies such as AWS or Azure for building and deploying models.
Strong experience with SQL for querying databases and manipulating data.
Experience working with libraries and frameworks such as Pandas, NumPy, Scikit-learn, and TensorFlow or PyTorch.
Solid understanding of machine learning algorithms, including regression, classification, clustering, and deep learning.
Familiarity with Generative AI and its applications will be an added advantage.
Experience in data visualisation tools such as PowerBI, Tableau, or Matplotlib.
Excellent problem-solving skills and ability to communicate complex ideas effectively to both technical and non-technical stakeholders.
Preferred Qualifications:
Experience with CI/CD pipelines for machine learning models.
Strong understanding of MLOps and managing machine learning lifecycle in production environments.
Certification in AWS or Azure (e.g., AWS Certified Machine Learning Specialty, Microsoft Azure AI Engineer Associate).
Familiarity with natural language processing (NLP) and deep learning models.
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