Senior Consultant, Data Science & AI

Toronto, Ontario, Canada
Remote
Posted Oct 28, 2026
1 position

$130,000–$160,000 / year

Opens an external site

Employment type: Full-time
Experience level: Senior · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week

Job summary

The Senior Consultant will design and deploy advanced machine learning models, generative AI solutions, and autonomous agentic workflows to solve complex client business challenges. They will also lead client workshops, synthesize complex data into actionable insights, and provide technical leadership to junior team members.

Job details

At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive. The position of Senior Consultant - Data Science & AI is within the TTEC Digital Analytics team. The Analytics group is responsible for Data Science, Advanced Analytics, Generative AI, and Engineering projects that include the design and validation of predictive models, building scalable machine learning pipelines, engineering autonomous agentic workflows, and leveraging enterprise Gen AI (LLMs, RAG architectures) to convert raw, unstructured client data into actionable insights that drive strategic business decision-making. Our Data Science & AI Consultants work directly with external clients, Data Engineers, Project Leads, and Managers on implementation, migration, and advanced analytics deployment projects. \n Key responsibilities Develop Machine Learning Models: End-to-end development, training, and deployment of production-grade predictive and prescriptive models (e.g., propensity modeling, customer segmentation, demand forecasting). Design & Deploy Generative AI Solutions: Architect, fine-tune, and evaluate enterprise Gen AI systems—including Retrieval-Augmented Generation (RAG) pipelines, custom LLM applications, and prompt engineering frameworks—to extract insights from unstructured data. Architect Agentic AI Systems: Design and deploy autonomous AI agents and multi-agent workflows capable of multi-step reasoning, tool utilization, and task automation to solve complex client business challenges. Deliver Advanced Analytics: Help clients maximize the efficiency of their strategic initiatives by building advanced analytics models that measure campaign performance, predict customer behavior, and maximize long-term ROI. Data Storytelling & Visualization: Synthesize complex algorithmic outcomes and machine learning metrics into compelling, executive-ready presentations and dashboards that clearly articulate business value and ROI. Develop and Maintain Analytics Workflows: 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 out data landscapes, and translate vague business problems into structured data science methodologies. Create solutions and design documentation for client data science architectures and ML pipelines. Work on projects independently as well as being part of a large team across multiple client engagements. Crosstrain Junior Data Scientists/Analysts or other team members with your area of expertise, providing technical leadership and code reviews. Further develop skills both on the job and through formal learning channels to stay ahead of AI/ML trends. Assist in pre-sales activities by scoping new client opportunities and providing accurate work/effort estimates. Skills and Experience Requirements 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 (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 (Core focus): Gemini Enterprise, Vertex AI Agent Builder, BigQuery ML, Model Garden (Model development, fine-tuning, and deployment) Data Engineering & Orchestration: BigQuery, Dataflow, and Cloud Storage for data extraction, pipeline management, and indexing BI & Data Visualization Tools: Looker / Looker Studio, Tableau, or Power BI MarTech/AdTech Ecosystems Agile/Scrum Methodologies CI/CD & MLOps/LLMOps: Version control, automated deployment pipelines, LLM evaluation, and model monitoring tools Personal: Strong interpersonal skills, high energy and enthusiasm, integrity, and honesty; flexible, results-oriented, resourceful, structured problem-solving ability, deal effectively with difficult client situations, ability to prioritize. Leadership: Ability to gain credibility, motivate, and provide leadership; work with a diverse external customer base; maintain a positive attitude. Provide technical support and guidance to more junior team members, particularly for challenging modeling or analytical assignments. Operations: Commercial acumen and ability to manage multiple projects simultaneously. Perform tasks in a client-friendly manner while utilizing time and resources efficiently, proactively managing project scope. Technical: Ability to understand, translate, and communicate highly complex technical and mathematical concepts to non-technical business stakeholders. \n $130,000 - $160,000 a year \n #LI-BN1 About Us TTEC Digital and our 1,800+ employees, pioneer engagement and growth solutions that fuel the exceptional customer experience (CX). Our sister company, TTEC Engage, is a 60,000+ employee service company, with customer service representatives located around the world. TTEC Holdings Inc. is the parent company for both Digital and Engage. When clients have a holistic need, they can draw from these independently managed centers of excellence, TTEC Digital and TTEC Engage. We are also delighted to share that TTEC has been awarded the Great Place To Work 2024-2025 certification based on outstanding employee experience across 14 countries. TTEC is a proud equal opportunity employer where all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability. TTEC has fully embraced and is committed to expanding our diverse and inclusive workforce. We strive to reflect the communities we serve while delivering amazing service and technology centered around humanity. Rarely do applicants meet all desired job qualifications, so if you feel you would succeed in the role above, please take a moment and share your qualifications. As part of our commitment to fair and efficient hiring practices, TTEC Digital uses artificial intelligence (AI) tools to help screen applications and match candidates to job requirements. These tools assist our human recruiters but do not make final hiring decisions. #LI-RemoteCanada

What you’ll do

Requirements

Candidates must have 5-8 years of experience in Data Science or Management Consulting, including at least 3 years in a client-facing role and 3 years of cloud-based model deployment. A post-secondary degree in a quantitative field is required, along with proficiency in Python, cloud platforms, and modern AI frameworks.