Senior Data Science Analyst - Capabilities & Insights

Role Overview: As a Data Scientist at QuantumBlack, you will be part of the LiveOps team, applying your data science expertise to assure sustainable impact of ML solutions developed. Your role will involve working alongside the LiveOps Lead and the LiveOps Engineer (Data Engineering) to continuously improve and maintain models deployed, resolving model-specific issues and integrating user feedback. Key Responsibilities: - Support ML solutions and manage the work with responsibility to ensure stability, continuity, and availability of the models, in addition to providing rapid response to incidents and escalated users queries. - Maintain, test, and improve existing machine learning solutions to ensure value capturing from model recommendations. - Monitor relevant metrics of machine learning models in production to identify potential issues, detect root causes, and define resolution actions. - Identify, research, and prioritize interventions to improve model efficiency based on feedback results from adoption. - Collect issues and feedback reported by end-users, collaborate with the scrum master to develop an intervention plan. - Proactively detect potential risks stemming from model adoption and plan for resolutions with the scrum master. - Own and prioritize individual Incidents, ensuring the delivery of solutions in line with Service Level Agreements and Operational Level Agreements to deadlines and quality standards, providing regular updates to key stakeholders at all levels. - Deliver documentation to agreed standards, on time and error-free. - Provide regional cover and support, offering expertise and specialized domain knowledge to allow resolution of key incidents during business hours. - Identify proactive remedial strategies to prevent future data problems and improve the quality of delivered solutions. - Engage in proactive and reactive monitoring and alerting. - Own and contribute to individual Service Improvement items including incident reduction and automation. Qualifications Required: - Graduate or postgraduate degree in computer science, engineering, applied mathematics, quantitative social sciences, or related field. - 2-5 years of relevant industry analytics experience. - Knowledge of ITIL processes. - Good understanding and hands-on experience in Python, Spark, and MLFlow. - Hands-on experience with SQL/MSSQL Database. - Good working knowledge of monitoring tools like Grafana and Splunk. - Working knowledge of Kedro is helpful. - Understanding of JIRA and Service Now tools. - Good to have working knowledge of any cloud provider - AWS/Azure/GCP. - Ability to work effectively with people at all levels in an organization. - Good to have knowledge of scheduling tools like Airflow and Argo. - Skills to communicate complex ideas effectively.,