Senior Data Scientist

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:

1. 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.

2. 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:

1. Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2. Certifications in AI, machine learning, or data engineering are a plus.
3. 5+ years of experience in data science, with a focus on machine learning and predictive analytics.
4. Proven experience deploying machine learning models in production environments.
5. Experience in incident management or operational optimization is highly desirable.
6. Strong programming skills in Python, R, and SQL.
7. Proficiency with machine learning frameworks like Scikit-learn, TensorFlow, or PyTorch.
8. Familiarity with cloud platforms (e.g., Azure, GCP, AWS) and MLOps tools.
9. Experience with ITSM platforms (e.g., ServiceNow) and monitoring tools (e.g., Splunk, Dynatrace).
10. Strong analytical and problem-solving skills.
11. Ability to work collaboratively in a cross-functional environment.
12. Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Preferred:

1. Hands-on experience in Predictive and Proactive Operations or similar domains.
2. Knowledge of incident, event, or workflow management processes.
3. Familiarity with SLA-driven operational environments.
4. Data-driven mindset with a focus on customer-centric solutions.
5. Proactive and adaptable, with a passion for continuous learning.
6. Collaborative and team-oriented, with a strong ability to work across departments.
7. Ability to design and implement models that enhance multi-system operational efficiency.
8. Focus on reducing IT operations incidents, false positive alerts, MTTR and improving SLA adherence.
9. 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

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