资深顾问,数据科学与AI
Senior Consultant, Data Science & AI
在TTEC Digital,我们指导客户,确保他们的员工感到被重视并得到充分支持,因为卓越的客户体验是一个以员工为先的过程。我们的愿景相同,是一个员工可以茁壮成长的地方。
高级顾问-数据科学与人工智能职位属于TTEC Digital分析团队。分析团队负责数据科学、高级分析、生成式AI和工程项目的实施,包括预测模型的设计与验证、构建可扩展的机器学习管道、工程自主代理工作流,并利用企业级生成式AI(大语言模型、RAG架构)将原始的非结构化客户数据转化为推动战略业务决策的可操作见解。
我们的数据科学与人工智能顾问会直接与外部客户、数据工程师、项目负责人和经理合作,开展实施、迁移和高级分析部署项目。
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关于我们
TTEC Digital及我们的1800多名员工,开创了促进参与和增长的解决方案,推动卓越的客户体验(CX)。我们的子公司TTEC Engage是一家拥有60000多名员工的服务公司,客户服务中心遍布全球。TTEC Holdings Inc.是Digital和Engage两家公司的母公司。当客户有全面需求时,他们可以从这两个独立管理的卓越中心TTEC Digital和TTEC Engage中获取资源。
我们也很高兴地分享,TTEC已获得2024-2025年最佳工作场所认证,这是基于在14个国家的出色员工体验。
TTEC是一家自豪的平等机会雇主,所有符合条件的申请人都将在不考虑年龄、种族、肤色、宗教、性别、性取向、性别认同、国籍和残疾的情况下获得就业考虑。TTEC已全面接受并致力于扩大我们的多元化和包容性员工队伍。我们努力反映我们服务的社区,同时提供以人类为中心的卓越服务和技术。
很少有申请人符合所有理想的职位要求,因此如果您认为自己能在上述职位中取得成功,请花点时间分享您的资格。
作为我们对公平高效招聘实践的承诺,TTEC Digital使用人工智能(AI)工具来帮助筛选申请并匹配候选人与职位要求。这些工具协助我们的招聘人员,但不会做出最终的招聘决定。
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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.
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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.
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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.