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Data Science Consultant 3
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Overview
Job Description
Job Description
In the assigned Job Role of Data Science Consultant 3, your Area Of Responsibility will be as below:
- Review data preparation tasks, and plans to address patterns or anomalies, while ensuring data readiness for advanced modeling and AI.
- Review models for complex use cases (e.g., forecasting models, LLM-based solutions), and refine algorithms to meet business needs.
- Review plan for smooth deployment into scalable, production-ready solutions.
- Review test plans and test results for analytics use cases, while defining optimization standards for model accuracy and stability, in alignment with business goals.
- Build models and analytics solutions tailored to business needs.
- Ensure quality and scalability across client engagements while actively contributing to knowledge assets and innovation streams.
- Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
- Review and refine analytics problems; identify data sources and extract from diverse environments.
- Oversee analysis execution and drive business insights.
- Create monitoring strategies across multiple projects, embedding governance frameworks to ensure robustness, reliability, and risk awareness.
- Review monitoring frameworks, refine documentation/reporting templates, and present insights on anomalies or slippages to stakeholders.
- Refine documentation strategy across teams, ensuring transparency and reproducibility of complex analytics solutions.
- Collaborate with cross-functional teams, ensuring alignment between analytics delivery and business strategy.
- Review analytics outputs for adherence to quality frameworks and project commitments.
- Recommend improvements to quality metrics and guide team members to align with standards.
- Identify and recommend model changes needed for successful deployment.
- Engage in creation and refinement of IP assets such as analytics prototypes and accelerators.
- Develop insights, whitepapers, and proof-of-concept summaries that highlight innovative thinking.
- Review innovative models and applications in non-ML, ML, deep learning, or LLM areas.
- Support participation in forums and internal knowledge exchanges.
- Deliver training sessions on technical and analytics-specific topics.
- Collaborate on content creation and mentor team members through hands- on guidance in live projects.
- Provide input for segment and unit-level business plans.
Your contribution to the team:
- A strong focus on innovation and scalable analytics solutions.
- Proactive problem-solving ability for complex, data-driven business challenges.
- Deep technical expertise across advanced modeling and AI use cases.
- A strategic mindset to align analytics with business goals.
- Ability to mentor team members and drive continuous improvement.
- Strong communication and knowledge-sharing capabilities.
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