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Why does this job exist and why is it critical?
The Data Scientist/ML Engineer Specialist is responsible for analysing complex datasets and developing AI models to provide actionable insights that drive strategic decision-making and business performance. This role focuses on applying advanced analytical techniques and AI methodologies to solve business problems and support the organization’s data-driven initiatives, with a specific emphasis on model monitoring to ensure ongoing model performance and reliability.
What are you accountable for?
Data Analysis and Machine Learning Development: Analyze large and complex datasets, perform exploratory data analysis (EDA), and build machine learning models such as segmentation, predictive, forecasting, recommendation engines, and NLP/computer vision solutions using programming languages like Python or R.
AI Model Deployment and Pipelines: Develop and deploy robust, scalable AI models and pipelines for batch processing or real-time APIs, ensuring seamless integration with downstream systems and timely project delivery.
Model Performance Monitoring: Track model accuracy, performance, and drift in production environments, ensuring reliability, relevance, and scalability to meet business needs.
Research and Innovation: Stay updated on state-of-the-art AI advancements, such as pre-trained LLMs, computer vision, and NLP techniques, applying them to enhance organizational capabilities and maintain competitive solutions.
Collaboration with Stakeholders: Engage with business stakeholders to gather requirements, align machine learning use cases with business objectives, and translate insights into actionable outcomes. Work closely with internal teams like data and ML engineering to ensure successful model deployment.
Documentation and Best Practices: Maintain comprehensive documentation of workflows, processes, and results to promote knowledge sharing, reproducibility, and adherence to best practices within the team.
Prompt Engineering and Gen AI: Optimize outputs from large language models (LLMs) using prompt engineering techniques to address domain-specific challenges and deliver high-quality, relevant solutions.
What do you need to have to fit this role?
Minimum 3-7 years of experience in data analysis, data science, or a related field.
Proficiency in statistical analysis, data visualization, machine learning (including advanced algorithms), computer vision, NLP, Gen AI, and programming.
Strong command of SQL, database concepts, and dimensional modeling. Experienced in data transformation methods across various data structures, including relational and unstructured data stores.
Possesses robust analytical and critical thinking skills.
A passionate self-starter who is highly dedicated and capable of working independently.
A strong team player with excellent interpersonal communication skills, proven ability to perform effectively under pressure, and dedicated to delivering results on time.
A background combining Telecommunication industry knowledge with relevant business experience is highly desirable.
What’s next?
Maxis values diverse voices & people. We hire and reward our employees based on capability & performance — regardless of ethnicity, gender, age, education, religion, nationality or physical ability.