Posted: 15 June
The role
Job Summary
Design, develop, deploy medium scale analytics models and AI applications that meet business and client outcomes, ensuring quality, innovation, and compliance with best practices.
Responsibilities
Design, develop, install, deploy, and test analytics models and AI applications.
Build and maintain training, feature engineering, and MLOps pipelines.
Build monitoring mechanisms and mitigate biases to ensure fairness.
Integrate models into production, develop APIs for access and predictions.
Implement monitoring, detect issues, and improve models iteratively.
Collaborate with data scientists, finance, actuaries, and engineers to achieve objectives.
Lead a data first approach, mentor others, and support Agile and SDLC processes.
Ensure data governance, security, and compliance throughout the lifecycle.
Qualifications
Bachelor's degree in a computing related discipline or equivalent experience.
7 10 years of industry experience, preferably senior software engineering and data analytics roles.
Proficient in Python, R, SQL, and data science programming.
Experience with data warehousing, relational and non relational databases, and cloud platforms.
Strong knowledge of AI/ML platforms (Dataiku, Amazon SageMaker, Azure Machine Learning).
Expertise in MLOps practices: model versioning, monitoring, deployment, and scalability.
Experience building pipelines, feature engineering, and model evaluation.
Understanding of bias detection, ethical AI, and governance principles.
Strong analytical, communication, and collaboration skills.
Preferred Skills
Leading understanding of AI, generative AI, machine learning algorithms, and statistical methods.
Experience with big data technologies and data streaming/event driven architectures.
Familiarity with MLOps, AIOps, DataOps, and Agile methodologies.
Knowledge of API integration and authentication for ML models.
Strong passion for continuous learning and improvement.
Job Category
Advanced Analytics
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