WaveAccess is looking for a Data Scientist – AI & Agentic systems. You will tackle real business challenges using a variety of data science methods, modern technology stacks, and cutting-edge techniques. In addition, you will help shape AI-driven features for our partners by assessing feasibility, researching agent-based AI solutions, defining data pipelines, and ensuring robust model training and optimization.
Responsibilities
AI Feature Development & Feasibility Analysis
- Work with product managers and engineers to evaluate potential AI-driven features for PACE IDP (Internal Development Platform)
- Assess feasibility, risks, and expected outcomes for AI implementations.
Agentic AI Research & Implementation
- Investigate and prototype agent-based AI models that can automate developer workflows within the IDP.
- Experiment with AI frameworks for building autonomous AI agents.
Data Strategy & Pipeline Development
- Define and implement data pipelines required for AI-driven features.
- Work with engineering teams to ensure data collection, storage, and processing align with model requirements.
Model Training & Optimization
- Develop, fine-tune, and deploy ML models that enhance developer experience within the platform.
- Optimize models for performance, cost-efficiency, and scalability
Close Collaboration
- Work closely with cross-functional teams to understand client requirements and achieve significant results
Requirements
- At least 3 years of experience as a Data Scientist
- English language proficiency at B2 level or higher
- Knowledge on DevOps, DevSecOps concepts – ES: this would be a great plus. Overall you are aware of the field PACE is working in – all about delivery , so this would help.
- In depth understanding on e2e LLM hosting and deployments of models
- Experience in implementation of RAG
- Presentation skills
Technologies
- Python, R, or Julia
- LLM
- Standard NLP stack
- Standard ML stack
- Basic SQL
- Git
- MLOps stack
- Vector databases (Postgres+pgvector / Milvus / Qdrant / Faiss)
Nice to Have
- Strong background in predictive analytics, NLP, and time-series modeling.
- Hands-on experience with MLOps, model deployment, and pipeline automation – ES: general understanding of how to deliver the models and their output to customers in the most efficient way.
- Knowledge of mathematical statistics
- Experience with S3
- Linux + bash, ssh
- Experience in written and verbal communication with business stakeholders
- Experience in full-cycle development
Would Be a Plus
- Experience developing RestAPIs
- Snowflake
- Docker
- Understanding of CI/CD
- Java/C++/other languages
We Offer
- Work in a dynamic international team
- Official employment, 100% paid sick leave and vacation
- Option to collaborate via sole proprietorship or self-employment
- Participation in international and Russian projects
- Voluntary health insurance with dental coverage
- All necessary equipment for work
- Corporate training programs
- Wide opportunities for self-realization, professional, and career growth
- A democratic approach to processes and a flexible start to the workday