The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Experience working with Databricks, Spark, Azure, AWS, or GCP”
The ad says“Experience working with Databricks, Spark, Azure, AWS, or GCP”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Experience working with Databricks, Spark, Azure, AWS, or GCP”
The ad says“Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows”
The ad says“Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation”
The ad says“Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Experience working with Databricks, Spark, Azure, AWS, or GCP”
The ad says“Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch”
The ad says“We are seeking a Lead Data Scientist, AI Engineering to lead the development of advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and technical leadership to deliver measurable business impact”
The ad says“Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation”
The ad says“We are seeking a Lead Data Scientist, AI Engineering to lead the development of advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and technical leadership to deliver measurable business impact”
The ad says“Advanced Python and SQL skills”
The ad says“Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection”
The ad says“Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows”
The ad says“Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch”
The ad says“Experience working with Databricks, Spark, Azure, AWS, or GCP”
The ad says“Advanced Python and SQL skills”
The ad says“Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation”
The ad says“Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch”
The ad says“Familiarity with transformer-based models and foundation-model applications”
The ad says“Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch”
We are seeking a Lead Data Scientist, AI Engineering to lead the development of advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and technical leadership to deliver measurable business impact
This role focuses on applying machine learning, predictive modelling, and foundation-model representations to solve business problems at scale. Typical use cases include forecasting, propensity modelling, recommendation systems, behavioural analytics, and customer intelligence
While familiarity with Generative AI is beneficial, this is primarily an applied machine learning and data science leadership role rather than a conversational AI, RAG, or agentic systems engineering position
Lead the design, development, and deployment of machine learning solutions that solve high-impact business problems
Define modelling approaches, experimentation frameworks, and success metrics for AI initiatives
Apply foundation-model embeddings and modern machine learning techniques to improve model performance and accelerate development
Drive projects from problem definition through model deployment and business impact measurement
Establish robust evaluation frameworks and benchmark new approaches against existing solutions
Partner with business, product, engineering, and analytics teams to identify and prioritise opportunities
Present technical findings and recommendations to stakeholders and senior leadership
Mentor and develop data scientists and AI engineers through technical guidance, reviews, and coaching
Contribute to hiring, capability development, and the long-term technical direction of the AI organisation
Preferred experience
Strong track record of delivering measurable business outcomes through machine learning
Experience solving predictive modelling problems such as attrition, forecasting, recommendation systems, propensity modelling, fraud detection, risk modelling, or customer analytics
Experience leading technical teams, mentoring practitioners, and influencing technical direction
Proven experience leading machine learning projects from concept through production deployment
Experience with machine learning frameworks such as Scikit-Learn, XGBoost, LightGBM, TensorFlow, or PyTorch
Familiarity with transformer-based models and foundation-model applications
Strong understanding of classification, regression, forecasting, recommendation systems, ranking, clustering, and anomaly detection
Strong expertise in machine learning, predictive analytics, statistical modelling, and experimentation
Experience with feature engineering, representation learning, embeddings, and downstream machine learning workflows
Advanced Python and SQL skills
Experience working with Databricks, Spark, Azure, AWS, or GCP
Leadership & Communication
Strong problem-solving and decision-making skills
Ability to translate complex technical concepts into actionable business insights
Ability to lead through influence across cross-functional teams
Excellent communication and stakeholder management capabilities
Experience leading technical projects or teams
8+ years of experience in machine learning, data science, AI, or advanced analytics
Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field
Experience developing and deploying machine learning models in production environments
Master’s degree or PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Mathematics, or a related field
Experience in financial services, payments, banking, fintech, fraud, marketing analytics, or customer intelligence
Experience with foundation models, embeddings, or representation learning
Publications, patents, conference presentations, or other evidence of technical thought leadership
