• Design scalable data processing pipelines for streaming and batch processing using Big Data technologies like Databricks, Airflow and/or Dagster. • Contribute to the development of CI/CD and MLOps processes. • Develop applications to aggregate, process, and analyze data from diverse sources. • Collaborate with the Data Science team on Machine Learning projects, including text/image analysis and predictive model building. • Develop and organize data transformations using Databricks/DBT and Apache Airflow. • Translate business requirements into technical solutions and ensure optimal performance and quality.

• Develop and maintain a high-performance data processing platform for automotive data, ensuring scalability and reliability. • Design and implement data pipelines that process large volumes of data in both streaming and batch modes. • Optimize data workflows to ensure efficient data ingestion, processing, and storage using technologies such as Spark, Cloudera, and Airflow. • Work with data lake technologies (e.g., Iceberg) to manage structured and unstructured data efficiently. • Collaborate with cross-functional teams to understand data requirements and ensure seamless integration of data sources. • Monitor and troubleshoot the platform, ensuring high availability, performance, and accuracy of data processing. • Leverage cloud services (AWS) for infrastructure management and scaling of processing workloads. • Write and maintain high-quality Python (or Java/Scala) code for data processing tasks and automation.

Role Description Within the telecommunications domain, we are actively seeking a Senior Data Scientist to strengthen our team focused on building AI-driven solutions that enhance customer experience and operational efficiency. - You will be working on advanced Generative AI use cases, including conversational AI (chatbots and voice bots), as well as internal AI tools that support business teams in their daily operations. - The role involves designing and scaling solutions such as RAG-based systems and intelligent assistants, enabling both customer-facing and internal automation scenarios. Qualifications - Master’s degree in AI, Machine Learning, Data Science, or a related field - 3–6 years of experience as a Data Scientist (preferably at Senior level) - Strong expertise in AI/ML and practical experience delivering business-impacting solutions - Hands-on experience with Generative AI, especially LLMs - Experience with NLP use cases (e.g. chatbots, voice bots, text processing) - Solid programming skills in Python and experience working with APIs, SQL, and Git - Experience designing and implementing production-ready solutions - Ability to communicate complex technical concepts to non-technical stakeholders Requirements - Experience with telecom domain or customer-facing digital products (nice-to-have) - Knowledge of Agentic AI, RAG systems, vector databases, and chunking strategies (nice-to-have) - Familiarity with LLM frameworks such as LangChain, LlamaIndex, LangGraph, AutoGen, or similar (nice-to-have) - Experience with AWS and/or on-premise deployments (nice-to-have) - Knowledge of Docker, Airflow, CI/CD pipelines (e.g. GitHub Actions/Runners) (nice-to-have) - Experience with Google AI/NLP ecosystem (nice-to-have) Benefits - At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. - We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. - By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.

• Work with our partners to understand business and technology problems and/or opportunities • Partner strongly with the head of data and the data team and data analysts. The head of data and data team will be responsible for setting a large amount of the requirements, but will hold short on technical design and physical modeling which this role will need to elaborate on. • Provide guidance and governance on standardized business logical data models, component re-use and platform modernization with an eye to designing business friendly views of data to empower citizen data scientists and BI users to leverage the data platform. • Lead the data design track, document and communicate solution that accommodate the Agile Principles of fail fast and provide the resilience necessary to accommodate changing and fluid requirements • In partnership with the data team, assist in the implementation of Data Governance Standards and Processes; partner with business stakeholders to establish a cadence in the upkeep of their information assets • Establish data domains for the Wealth/Global Investments business for reuse, standardization and security-by-design into your designs to simplify, secure and enable accelerated solution delivery. • Assist in the establishment of a self-governance operating model to manage data models and catalogs for the wealth/global investments business. • Bring a shift left mentality in maintenance of the business data terms, critical data elements as well as business rules. • Introduce learning capsules to enable self service capabilities for management of business data catalog and allied assets • Be innovative in your design thinking and use your expertise to influence the MMC technology roadmap • Take your architectural designs through our on boarding processes to ensure they meet MMCs standards and conventions • Participate in architecture reviews as part of MMCs Architecture Assurance process • Support the implementation of architectural designs from infrastructure set up through to delivery as necessary • Empower the development teams to deliver your architectural designs with a light touch approach • Be an involved member in our technology community, championing the latest technologies and trends within MMC and the wider industry, sharing your knowledge, successes and learnings with your colleagues. • Run the software delivery Pod ensuring there are smooth and efficient processes for getting software through from requirements to working in production focussing on value creation, growth and serving customers • Makes outcomes that leads to project success, and work with Product Owner and Business Analysts to help project team prioritize and groom backlog in order to deliver an Alpha early, then continue to deliver value often throughout the project lifecycle to staging and production environments. • You will have an Enterprise mind-set able to foster collaboration, break down silos, identify and work to remove blockers • You will be intimately familiar with the Agile processes and practices required for successful and sustainable delivery. • Solid understanding of Software Development, Architecture, Test Engineering and Security best practice in an Agile environment • Pods support the full lifecycle of a product and we operate on the philosophy that the work comes to the team. You will need to consider tech debt, obsolescence, security and modernisation • Working with the wider team to plan complex product releases • Ensure our standard metrics are visible and actively being used to drive drawing conclusions • Own the Continuous Improvement backlog for the Pod. This is the key mechanism by which we deliver improvements for the following: time to market, efficiency and quality