About the Role:
As a Data Scientist in AI operations Team, you'll play a crucial role in supporting data-driven projects, performing routine data analysis tasks, and assisting with model development and testing. Your role involves contributing to various stages of the data science lifecycle and providing insights that help shape business strategies. This position is suited for those with a foundational understanding of data science and are eager to deepen their expertise.
Responsibilities:
Develop, deploy, and maintain robust machine learning models using traditional techniques (e.g., scikit-learn) to support AI-driven operations.
Conduct root cause analyses to identify and resolve data inconsistencies and performance bottlenecks.
Collaborate extensively across engineering, product, and business teams to align AI solutions with operational goals.
Integrate Gen AI capabilities (LLMs, SLMs, Agents) using frameworks like LangChain and LangGraph to enhance automation and decision-making.
Create insightful visualizations and dashboards to communicate findings and model performance.
Participate in feature engineering and model tuning to improve accuracy and reliability.
Ensure data integrity and consistency across multiple sources and systems.
Mentor junior team members and foster a culture of continuous learning and innovation.
Skills:
Python Expertise: Advanced proficiency in Python for data manipulation, modeling, and automation.
Traditional ML: Strong hands-on experience with scikit-learn and other classical ML libraries.
Gen AI Knowledge: Familiarity with LLMs, SLMs, and agent-based architectures using LangChain, LangGraph, or similar tools.
Data Engineering: Experience building and optimizing data pipelines and workflows.
Visualization: Skilled in tools like Matplotlib, Seaborn, Power BI, or Tableau.
Database Proficiency: Strong SQL and working knowledge of NoSQL databases.
Communication: Ability to clearly articulate technical concepts to non-technical stakeholders.
Collaboration: Proven ability to coordinate across teams and manage dependencies effectively.
Mentorship: Experience guiding junior data scientists and contributing to team development.
Level criteria T2 (for internal use only):
• 3+ Years of experience, with working knowledge and expanded conceptual knowledge in primary technical job family and broadens capabilities; has worked with and is proficient with current technologies
• Understands key business drivers and builds knowledge of the company, processes and customers
• Performs a range of technical assignments and solves moderately complex problems under guidance of established policies and procedures
• Receives a moderate level of guidance and direction
• Impacts quality of own work and the work of others on the team; may provide informal guidance to new team members
• Explains complex information to others in straightforward situations
Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
