Verified Job
Work from home
Assistant Lead Engineer
Work from home
#708116
Remote / WFH
Job Description
Responsibilities:
• Translates data-related client requirements into project tasks and deliverables, with an understanding of complex problems and solutions.
• Drives data solutions within projects, with a focus on innovation and value creation.
• Provides technical guidance and support to team members on data science methodologies, tools, and algorithms.
• Acts as a point of escalation for data science-related issues within the project, working towards efficient resolution.
• Reviews and ensures adherence to performance parameters for data science tasks, with a focus on data quality and model performance.
• Balances data science workload within the team, considering the skills and capacities of team members.
• Champions learning initiatives for upskilling and cross-skilling in data science within the team, including knowledge sharing sessions and promoting best practices.
• Contributes to the development of new data science solution offerings, leveraging insights from project work.
• Encourages team members to build technical expertise and innovate within the realm of data science.
• Begins to build and nurture client relationships with a focus on identifying opportunities to add value through data science.
• Starts to develop proficiency in at least one of data engineering, MLOps, product engineering, and cloud services, and applies this knowledge within projects.
• Begins to contribute to the organisation's thought leadership in data science, such as writing articles, giving presentations, or contributing to internal forums.
• Actively identifies and communicates opportunities for the organisation to enhance its data science capabilities, including new tools, methodologies, or service offerings.
• Keeps an eye on industry trends in data science to ensure personal growth and the competitive advantage of the organisation.
Requirements:
• Demonstrates proficiency in at least one of the four areas: Computer Vision, Natural Language Processing, Machine Learning, and Forecasting.
• Expected to deepen this expertise further.
• Translates data-related client requirements into project tasks and deliverables, with an understanding of complex problems and solutions.
• Drives data solutions within projects, with a focus on innovation and value creation.
• Provides technical guidance and support to team members on data science methodologies, tools, and algorithms.
• Acts as a point of escalation for data science-related issues within the project, working towards efficient resolution.
• Reviews and ensures adherence to performance parameters for data science tasks, with a focus on data quality and model performance.
• Balances data science workload within the team, considering the skills and capacities of team members.
• Champions learning initiatives for upskilling and cross-skilling in data science within the team, including knowledge sharing sessions and promoting best practices.
• Contributes to the development of new data science solution offerings, leveraging insights from project work.
• Encourages team members to build technical expertise and innovate within the realm of data science.
• Begins to build and nurture client relationships with a focus on identifying opportunities to add value through data science.
• Starts to develop proficiency in at least one of data engineering, MLOps, product engineering, and cloud services, and applies this knowledge within projects.
• Begins to contribute to the organisation's thought leadership in data science, such as writing articles, giving presentations, or contributing to internal forums.
• Actively identifies and communicates opportunities for the organisation to enhance its data science capabilities, including new tools, methodologies, or service offerings.
• Keeps an eye on industry trends in data science to ensure personal growth and the competitive advantage of the organisation.
Requirements:
• Demonstrates proficiency in at least one of the four areas: Computer Vision, Natural Language Processing, Machine Learning, and Forecasting.
• Expected to deepen this expertise further.
