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Senior Consultant, Data Science – AI
TTEC Digital. Develop, train, and deploy production-grade predictive and prescriptive machine learning models.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying predictive and prescriptive machine learning models, with a strong focus on Generative AI systems and cloud environments. Capable of translating complex data science methodologies into actionable insights for clients while providing technical leadership and mentoring to junior team members.
Highest-signal resume keywords
Generative AI System ArchitectureCloud Environment DeploymentPredictive Model DevelopmentClient-Facing Consulting ExperienceGoogle Cloud Certification
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Machine LearningPredictive AnalyticsData Science MethodologiesAdvanced SQLPython (pandas, numpy, scikit-learn, XGBoost, PyTorch, TensorFlow)Generative AI FrameworksVector DatabasesData Extraction and Pipeline ManagementAnalytics Model DesignPrompt Engineering
Soft Skills
Interpersonal SkillsStructured Problem-SolvingResults OrientationFlexibilityResourcefulness
Tools & Technologies
Google Cloud PlatformBigQueryLooker/Looker StudioTableauPower BIDataflowCloud StorageGemini EnterpriseVertex AI Agent BuilderModel Garden
Certifications & Qualifications
Google Cloud Certified Professional Data EngineerProfessional Machine Learning Engineer
Industry Keywords
MarTechAdTechAgileScrumCI/CDMLOpsLLMOps
Tech Stack
Tools & technologiesBigQueryCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchScikit-LearnSQLTableauTensorflow
About the role
Key responsibilities & impact- Develop, train, and deploy production-grade predictive and prescriptive machine learning models.
- Architect, fine-tune, and evaluate enterprise Generative AI systems, including RAG pipelines, custom LLM applications, and prompt engineering frameworks.
- Design and deploy autonomous AI agents and multi-agent workflows for complex client business challenges.
- Build advanced analytics models to measure campaign performance, predict customer behavior, and maximize long-term ROI.
- Translate machine learning metrics and algorithmic outcomes into executive-ready presentations and dashboards.
- Analyze raw client data and build optimized analytics datasets within cloud environments.
- Lead external-client workshops to identify objectives, map data landscapes, and translate business problems into data science methodologies.
- Create solution and design documentation for client data science architectures and ML pipelines.
- Work independently and as part of large teams across multiple client engagements.
- Cross-train junior Data Scientists/Analysts and provide technical leadership and code reviews.
- Continue developing AI/ML skills through on-the-job and formal learning.
- Support pre-sales by scoping client opportunities and estimating work and effort.
Requirements
What you’ll need- Post-Secondary Degree (or Diploma) related to 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 and Agentic AI workflows.
- 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.
- Experience with Python stack: pandas, numpy, scikit-learn, XGBoost, PyTorch/TensorFlow, Transformers.
- Experience with Generative and Agentic AI frameworks, including LangChain, LlamaIndex, AutoGen/CrewAI, prompt engineering, RAG architectures, multi-agent orchestration, function calling, and tool integration.
- Experience with vector databases and search technologies, including BigQuery Vector Search, Google Cloud Vector Search, Pinecone, Chroma, or FAISS.
- Advanced SQL query optimization for large-scale data warehouses.
- Experience with Google Cloud Platform, including Gemini Enterprise, Vertex AI Agent Builder, BigQuery ML, and Model Garden.
- Experience with BigQuery, Dataflow, and Cloud Storage for data extraction, pipeline management, and indexing.
- Experience with Looker/Looker Studio, Tableau, or Power BI.
- Knowledge of MarTech/AdTech ecosystems, Agile/Scrum methodologies, and CI/CD & MLOps/LLMOps.
- Strong interpersonal skills, integrity, flexibility, results orientation, resourcefulness, structured problem-solving, prioritization, and ability to handle difficult client situations.
- Ability to provide technical leadership, mentor junior team members, manage multiple projects, and communicate complex technical and mathematical concepts to non-technical stakeholders.
Benefits
Comp & perks- Equal opportunity employer
- Diverse and inclusive workforce
- Great Place To Work 2024-2025 certified employer
- Formal learning channels and on-the-job skill development