Accountabilities
- Design and develop machine learning models for anomaly detection, predictive analytics, root cause analysis, and failure prevention.
- Guide the development of technical roadmaps and strategies for AI platforms and large-scale LLM integration, driving innovation in AI applications and tools.
- Research and explore new NLP techniques and technologies to stay at the forefront of the field.
- Implement self-healing systems by integrating AI/ML models with IT automation platforms (e.g., Ansible, ServiceNow).
- Leverage tools like Snowflake, DBT, DataIku, and Fivetran to optimize data pipelines and enhance data observability.
- Develop dashboards to visualize AI/ML model insights and provide actionable recommendations for partners.
- Work with large-scale IT operational data (logs, metrics, events) to extract insights.
- Collaborate with multi-functional teams to define project requirements and work.
- Communicate effectively with partners to understand their needs and provide technical insights.
- Present project updates, results, and recommendations to senior management.
- Handle data effectively from different sources and build scripts that will make the custom data platform flexible and scalable across data sets.
- Pilot and implement innovative AI technologies to enhance the organization's observability framework.
- Familiarity with MLOps practices (CI/CD pipelines for ML).
- Make use of specialist tools and statistical methods to extract the data needed, research new ways to make use of the data, respond to data-related queries and analyze to identify trends.
- Strong problem-solving and critical-thinking skills to diagnose and resolve complex IT issues.
- Good communication and presentation skills to convey technical insights to partners.
Essential Skills/Experience
- 9-12 years of IT experience but 3-5 years of relevant data and insight experience.
- Solid experience in EDA (Exploratory Data Analysis), SQL, and programming with Python/R.
- Higher education with demonstrated capability to perform in a complex IT environment.
- Prior experience in an Information Services/Information Technology environment with good business acumen.
- Experience of working within a quality and compliance environment and application of policies, procedures, and guidelines.
- Evidence of designing, testing, and maintaining solutions.
- Experience of sharing knowledge/information and implementing any changes.
- Well versed in ITIL V3.0 practices and process.
- Good experience and/or awareness and/or drive in/to create actionable insights for IT Operations from IT systems that can support the operations of a world-class IT function.
- Global engagement exposure or working in a distributed team.
- Good team player and partner engagement.
- Experience of Data Analysis enabling tool kits.
- Data Handling (ETL), Data Insight Experience.
- Statistical Methods.
- Snowflake, DBT, Collibra.
- PowerBI, Grafana.
- DBT and DataIku.
- AI and Machine Learning implementation experience.
- Python or R.
- Awareness of the end-to-end processes and activities in the build and support of Data solutions.
- Experience in the use of metadata cataloguing tools.
Desirable Skills/Experience
- Degree level education in computer science or Masters.
- Demonstrate initiative, strong customer orientation, and cross-cultural working.
- Splunk (Search expert, data science analyst, developer role).
- GxP, SOX compliance.
- Quality and Audit exposure (D).
- Experienced in applying a risk-based methodology to data and information management.