Data Science & MLOps Section Manager

Vakansiyanın detalları

Lead, mentor, and inspire a team of Data Scientists and MLOps Engineers to develop AI/ML-driven solutions across customer analytics, revenue optimization, and operational efficiency.
Drive the adoption of cutting-edge AI/ML techniques, including deep learning transformers and Generative AI for telecom-specific use cases.
Oversee the full AI/ML lifecycle, from experimentation and model development to deployment and monitoring in production.
Champion the implementation of MLOps best practices, ensuring robust CI/CD framework, experimentation tracking, model monitoring, and automated retraining strategies.
Support the adoption and governance of enterprise AI/ML platforms such as AWS SageMaker, Dataiku, or Databricks to streamline development and deployment workflows.
Drive research and implementation of Parameter-Efficient Fine-Tuning (PEFT) methods and prompt engineering strategies for optimizing GenAI models.
Collaborate closely with BI and Data Engineering to ensure seamless integration of AI/ML solutions into enterprise data and analytics ecosystems.
Define and enforce model governance, risk management, and explainability practices to enhance AI trust and compliance.
Partner with business teams to identify high-impact AI/ML opportunities and translate them into actionable solutions.
Stay up to date with the latest advancements in GenAI, NLP, and MLOps to ensure the company remains at the forefront of innovation.

Proven experience leading Data Science and MLOps teams.
Strong background in machine learning, deep learning, NLP and Generative AI (LLMs).
Hands-on experience with modern AI/ML platforms such as AWS SageMaker, Dataiku, Databricks or similar.
Expertise in MLOps, CI/CD pipelines, MLflow/Kubeflow and Orchestration frameworks.
Experience with TensorFlow/PyTorch, Scikit-learn, Keras or MXNet
Experience with vector databases and retrieval-augmented generation (RAG) implementations.
Experience with cloud environments (AWS, Azure, or GCP) and hybrid AI/ML deployments is an asset
Work experience with big data processing frameworks such as Spark or Hadoop is an advantage.
Telecom industry experience is a strong plus.
Fluency in English or Russian (knowledge of a second foreign language is an asset).
Skills and Competencies:
Passionate about AI/ML, MLOps/LLMops, and staying ahead of industry trends.
Strong problem-solving and analytical skills with the ability to drive business impact through AI.
Excellent communication and stakeholder management skills, bridging the gap between technical and business teams.
Strategic thinker with a hands-on approach to execution.