TD
Senior Consultant, Data Science & AI
TTEC Digital
Contract type
Ongoing
Work mode
Hybrid · Hybrid (inferred: EU/NL where applicable)
Experience
Senior · 5+ years
Job description
Key details
- Develop end-to-end machine learning models for production, including predictive and prescriptive models such as propensity modeling, customer segmentation, and demand forecasting
- Architect, fine-tune, and evaluate enterprise Generative AI systems, including Retrieval-Augmented Generation (RAG) pipelines, custom LLM applications, and prompt engineering frameworks
- Design and deploy autonomous AI agents and multi-agent workflows capable of multi-step reasoning, tool utilization, and task automation
- Build advanced analytics models to measure campaign performance, predict customer behavior, and maximize long-term ROI
- Synthesize complex algorithmic outcomes and machine learning metrics into executive-ready presentations and dashboards
- Analyze raw client data and build optimized analytics datasets within cloud environments to support modeling and reporting
- Lead workshops with external clients to uncover business objectives, map data landscapes, and translate business problems into structured data science methodologies
- Create solutions and design documentation for client data science architectures and ML pipelines
- Work independently and as part of a large team across multiple client engagements
- Crosstrain junior data scientists/analysts and provide technical leadership and code reviews
- Further develop skills through on-the-job and formal learning to stay ahead of AI/ML trends
- Assist in pre-sales activities by scoping new client opportunities and providing accurate work/effort estimates
- Company mission
- Information not specified
Primary stack
Core technologies
Python (Programming Language)SQLGoogle Cloud Platform (GCP)
Benefits
- Information not specified
Requirements & details
- Post-secondary degree or diploma in Data Science, Statistics, Computer Science, Economics, Business Analytics, or an IT-related field
- 5–8 years of total experience in Data Science, Advanced Analytics, or Management Consulting
- 3+ years of experience in an external client-facing consulting or professional services capacity
- 3+ years of application, model design, and deployment experience natively within a cloud environment (GCP preferred)
- 1–2+ years of hands-on experience architecting and deploying Generative AI systems (e.g., RAG pipelines, fine-tuned LLMs) and Agentic AI workflows (e.g., autonomous agents, tool-use integration)
- Demonstrated experience delivering both traditional predictive models and modern AI solutions to enterprise stakeholders
- Google Cloud Certified Professional Data Engineer, Professional Machine Learning Engineer, or equivalent Generative AI/Cloud Certifications (highly preferred)
- Python stack: pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow, Transformers
- Generative & Agentic AI frameworks: LangChain, LlamaIndex, AutoGen/CrewAI, prompt engineering, RAG architectures, multi-agent orchestration, function calling & tool integration
- Vector databases & search: BigQuery Vector Search, Google Cloud Vector Search, Pinecone, Chroma, or FAISS
- SQL: advanced query optimization for large-scale data warehouses
- Google Cloud Platform experience
- Python, pandas, numpy, scikit-learn, XGBoost, PyTorch, TensorFlow, Transformers, LangChain, LlamaIndex, AutoGen, CrewAI, BigQuery Vector Search, Google Cloud Vector Search, Pinecone, Chroma, FAISS, SQL, Google Cloud Platform
- Python (Programming Language)
- SQL
- Google Cloud Platform (GCP)
