Ford Business Solutions (FBS) is a global organization providing centralized support to the business in various areas utilizing it global footprint. In Europe, FBS operates providing service in Marketing & Sales, Finance (Controlling), Aftersales, HR, and Customer Relationship Center in Hungary, and Ford Credit and Enterprise Technology in Romania. 

These FBS locations operate as Centers of Expertise in these areas with deep business acumen working hand-in-hand with their counterparts mainly in the European or Global Headquarters and the various European markets.

This position was created to fast track our AI/ML and AI Agent development journey to create efficiency, increase productivity, and improve our colleagues every day. The FBS Europe Data & Tech Lead is expected have a robust understanding of the wide range of options in the AI/ML and Low-Code/No Code (LCNC) to advise the various teams on which option is used best. The person is expected to gain a good understanding of the various processes, identify AI/ML and LCNC opportunities, and prioritize them. After aligning the priorities with the Center Leadership Team, the person is expected to work closely with the business teams to create a technical specification that can be channeled to the coders in India. The person should build a bridge between the businesspeople and the IT teams, translating their needs so they understand each other, be involved in the testing and implementation. 

In addition, the person is expected to pull a virtual team together relying on colleagues interested in AI/ML and Business Data Analysts, involve them in various projects so their AI/ML knowledge is grown and therefore the speed of automation, simplification can gain speed. 

Technical skills: 

Strong background in machine learning, analytics, and leadership to spearhead our data science initiatives. The ideal candidate will have an advanced degree in a quantitative discipline and a proven track record in deploying scalable machine learning models, including expertise in NLP. This role requires a strategic thinker with experience in managing a team, leveraging advanced analytics tools, and implementing ML Ops, particularly on the Google Cloud Platform (GCP). 

Proficient in data manipulation and computational libraries: Pandas, Numpy, Scikit-Learn. Experienced with deep learning frameworks: Pytorch, TensorFlow, Keras. Skilled in analytics and visualization tools: Alteryx, Qlik, Tableau, PowerBI. Familiar with database management: SQL, NoSQL. Proficient in cloud computing platforms, with a focus on GCP for ML Ops deployments. Experienced with Big Data technologies: Hadoop, Spark. Solid understanding of programming/ scripting languages: Python/ R ; C/C++, Java, (Optional) Familiar with development and version control tools: Git, CI/CD pipelines.

AI Agent Specific Technical Skills:

Deep understanding of Large Language Models (LLMs), including prompt engineering, fine-tuning techniques and Retrieval Augmented Generation (RAG) patterns. Experience with AI agent development frameworks and libraries (e.g., LangChain)  Knowledge of vector databases (e.g., Pinecone, FAISS) for semantic search, knowledge retrieval. Understanding of agent architectures, including concepts like planning (e.g., ReAct, Tree of Thoughts), tool use/function calling, and multi-agent systems.

Soft skills:

Demonstrated ability to act as a liaison or bridge between business stakeholders and technical development teams, particularly in cross-cultural or offshore contexts (experience working with teams in India is a strong plus). Exceptional communication, interpersonal, and relationship-building skills, capable of effectively interacting with both technical and non-technical audiences across different organizational levels and cultural backgrounds. Proven ability to mentor, coach, and provide hands-on guidance to colleagues with varying technical backgrounds. Experience in building or participating in communities of practice, user groups, or internal knowledge-sharing initiatives. Proven ability to work independently, manage multiple priorities, and drive initiatives forward with a high degree of self-motivation. Experience in documenting and presenting technical concepts and project successes to non-technical audiences. Bachelor’s or master’s degree in computer science, engineering, business information systems, or a related technical or business field, or equivalent practical experience.

Preferred Skills:

Holds an MS/PhD in Computer Science, Operational Research, Statistics, Applied Mathematics, or related fields.  Demonstrated experience in feature engineering, hyper-parameter tuning, model evaluation, and NLP. Strong theoretical understanding of machine learning, text mining techniques, detection, segmentation, probabilistic algorithms, and optimization. Experience in publishing in recognized Machine Learning journals/conferences. Six Sigma certification or equivalent is an advantage.

Please note that we currently run background checks as part of our recruitment process pending a successful interview.

We are looking for a Data Science Manager with a strong background in machine learning, analytics, AI agent design, and leadership to spearhead our data science initiatives. The ideal candidate will have an advanced degree in a quantitative discipline and a proven track record in deploying scalable machine learning models, including expertise in NLP. This role requires a strategic thinker who can engage larger teams, leverage advanced analytics tools, and implement ML Ops, particularly on the Google Cloud Platform (GCP), and guiding the development of autonomous or semi-autonomous agentic systems.

Business Understanding & Strategic Opportunity Identification: Proactively engage with various skill teams and departments to gain a deep understanding of their operations, challenges, and processes. Independently identify high impact/ low effort opportunities where AI/ML or LCNC solutions can deliver significant value, efficiency gains, or process improvements. Requirements Definition & Solution Design: Work closely and collaboratively with business stakeholders in Hungary to translate identified opportunities into clear, detailed, and actionable technical requirements and user stories for potential solutions. Leverage his/her technical expertise to help define the appropriate approach (AI/ML, LCNC, or a combination) and platform. Cross-Cultural Bridge Building & Liaison (Hungary-India): Serve as the primary liaison and communication channel between business teams in Hungary and the GDIA development team in India. Foster a strong, collaborative working relationship, facilitating effective communication, clarifying requirements, managing expectations, and building mutual understanding across time zones and cultures. Solution Development Facilitation & Oversight: Work closely with the GDIA team in India to guide the development of the solutions based on the defined requirements. Provide technical context, answer questions, and ensure the developed solution aligns with specifications and platform best practices. Testing and Validation: Lead and actively participate in the testing and validation of developed solutions alongside the business users in Hungary. Ensure the solution meets the defined requirements, is user-friendly, and delivers the intended business value. Gather feedback and coordinate with the GDIA team on necessary adjustments. Virtual AI/ML & LCNC Team coordination:  Building & Leading a Virtual AI/ML & LCNC Community: Identify and engage interested individuals from Skill Teams and Business Analytics & Reporting employees to form a virtual community of practice. Foster a collaborative environment for sharing knowledge and exploring potential applications. Promote continuous learning in the virtual team on latest data science techniques, AI agent frameworks, and tools. Mentorship & Hands-On Assistance: Provide hands-on guidance, assistance, and mentorship to members of the virtual community. Help them apply AI/ML and LCNC concepts to their own work, assisting with tool usage, problem-solving, and developing their practical skills in these areas. Knowledge Development & Sharing: Actively work to develop the knowledge and capabilities of the virtual team members through informal training, workshops, sharing sessions, and curated resources. Strategic Reporting & Internal Showcasing: Actively work with the Process Re-engineering (PRE) team on efficiency improvement ideas and identifying where AI/ML and LCNC solutions could be used.  Based on successful projects (both those you directly facilitated and those enabled by the virtual team), identify and document efficiency opportunities. Proactively notify the Process Reengineering (PRE) Team of these opportunities to ensure they are recorded and considered for broader process improvements. Collaborate with the FBS Communications team to create visibility around successful initiatives and projects. Develop compelling showcase examples and case studies of implemented solutions to share across the organization, sparking further ideas and demonstrating the value of AI/ML and LCNC. Technical Expertise: Maintain extensive hands-on knowledge and stay current with a wide range of AI/ML techniques, tools, and platforms (e.g., data science methodologies, machine learning algorithms, cloud AI services), AI Agent development frameworks and concepts (e.g., LLM-based agents, planning, tool use, memory) and LCNC platforms (e.g., Microsoft Power Platform, OutSystems, Mendix, Appian, etc.). Apply this knowledge to guide project work and mentor the community. Independent Drive: Operate with a high degree of autonomy, managing your own workload, prioritizing opportunities, leading projects, and cultivating the virtual community with minimal direct supervision.