Overview:
The Senior Data Scientist will play a critical role in driving the development of AI and machine learning models to enhance Predictive and Proactive Operations. The role requires a blend of technical expertise, analytical thinking, and collaborative skills to create innovative data-driven solutions that optimize incident management workflows, improve SLA adherence, and reduce MTTR. The Senior Data Scientist will work closely with cross-functional teams and contribute to building a robust and efficient operational framework.

Key Responsibilities:
Data Science and Model Development:
• Design and implement predictive and prescriptive models to address operational challenges.
• Develop algorithms to optimize multi-system incident workflows and improve SLA compliance.
• Collaborate with data engineers to build scalable data pipelines and ensure efficient data processing.

Incident Management Solutions:
• Apply advanced analytics to enhance end-to-end incident workflows across multiple systems.
• Leverage machine learning to automate detection, triage, and escalation processes.
• Monitor and fine-tune models to ensure accuracy, efficiency, and reliability.
• Partner with product teams, service delivery managers, and architects to align solutions with business goals.
• Act as a subject matter expert in data science, providing insights and recommendations to improve processes.
• Translate business requirements into actionable data science solutions.
• Analyze existing processes to identify inefficiencies and propose data-driven enhancements.
• Stay updated on industry trends, tools, and technologies to incorporate best practices into the team’s work.
• Contribute to building a library of reusable models and solutions to support the broader organization.
• Develop dashboards and reports to visualize insights, track SLA adherence, and measure MTTR improvements.
• Communicate findings and progress to both technical and non-technical stakeholders effectively.

Qualifications:
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Certifications in AI, machine learning, or data engineering are a plus.
• 5+ years of experience in data science, with a focus on machine learning and predictive analytics.
• Proven experience deploying machine learning models in production environments.
• Experience in incident management or operational optimization is highly desirable.
• Strong programming skills in Python, R, and SQL.
• Proficiency with machine learning frameworks like Scikit-learn, TensorFlow, or PyTorch.
• Familiarity with cloud platforms (e.g., Azure, GCP, AWS) and MLOps tools.
• Experience with ITSM platforms (e.g., ServiceNow) and monitoring tools (e.g., Splunk, Dynatrace).
• Strong analytical and problem-solving skills.
• Ability to work collaboratively in a cross-functional environment.
• Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Preferred:
• Hands-on experience in Predictive and Proactive Operations or similar domains.
• Knowledge of incident, event, or workflow management processes.
• Familiarity with SLA-driven operational environments.
• Data-driven mindset with a focus on customer-centric solutions.
• Proactive and adaptable, with a passion for continuous learning.
• Collaborative and team-oriented, with a strong ability to work across departments.
• Ability to design and implement models that enhance multi-system operational efficiency.
• Focus on reducing IT operations incidents, false positive alerts, MTTR and improving SLA adherence.
• Contribution to building scalable and reusable data science solutions.

Offer due date: 2025-01-04

Start date: 2025-01-06

End date: 2025-12-31