CX Data Scientist
Budapest, Kozep-Magyarorszag, Hungary
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Ford Motor Company
Since 1903, we have helped to build a better world for the people and communities that we serve. Welcome to Ford Motor Company.Contribute to the evolution of our Customer Experience (CX) by leveraging data-driven insights and advanced analytics. This role is pivotal in designing, building, and maintaining robust data solutions on the Google Cloud Platform (GCP). You will be instrumental in transforming raw data, including eg. connected vehicle data, into actionable intelligence, enabling the development of innovative CX solutions such as automated dashboards, AI-powered chatbots, and personalized customer interactions. Your expertise and end to end ownership will empower various CX teams to make informed decisions and continuously improve the customer journey.
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes on Google Cloud Platform (GCP) to ingest, process, and store data from diverse sources, ensuring data quality and reliability.
- Leverage expert-level SQL and Python skills for complex data extraction, transformation, cleansing, and analysis, with a strong focus on preparing data for analytical and machine learning applications.
- Develop, deploy, and monitor machine learning models and AI-driven solutions (e.g., predictive analytics, natural language processing for chatbots, anomaly detection) using GCP AI Platform (Vertex AI) and other relevant AI APIs.
- Architect and manage data structures and tables within GCP (e.g., BigQuery, Cloud SQL, Spanner), optimizing for performance, cost, and accessibility for various CX use cases.
- Create and automate the generation of insightful dashboards and reports (e.g., using Looker, Power BI, or Qlik Sense) for CX performance tracking, connected vehicle data exploration, and ad-hoc analyses.
- Collaborate closely with CX Performance Managers, Analysts, Product Owners, and other stakeholders to understand data requirements, define project scope, and deliver data solutions that meet business needs.
- Explore and analyze large datasets, including eg. vehicle maintenance data, to uncover trends, patterns, and insights that can inform CX strategy and product development.
- Lead and support data projects involving the use of AI APIs (e.g., Google Cloud AI APIs like Dialogflow, Natural Language API, Vision API) to build innovative CX tools and functionalities.
- Ensure data governance, security, and compliance best practices are implemented and adhered to for all data solutions, particularly concerning customer data and PII.
- Provide technical guidance and mentorship to other team members on data engineering best practices, GCP services, and AI/ML techniques.
- Stay current with emerging technologies and advancements in data engineering, data science, AI/ML, and the Google Cloud Platform ecosystem, and advocate for their adoption where beneficial.
- Document data architectures, data flows, model specifications, and processes to ensure clarity, maintainability, and knowledge sharing within the team.
- Degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a comparable quantitative field (Bachelor's degree required; Master's or PhD is desirable).
- Proven hands-on experience as a Data Engineer or Data Scientist, with a significant portfolio of projects involving data pipeline development, data modeling, and deploying solutions on cloud platforms.
- Expert proficiency in SQL and Python, including common data science and machine learning libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
- In-depth knowledge and practical experience with Google Cloud Platform (GCP) data services, including but not limited to BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Functions, Vertex AI, and Looker.
- Strong understanding of data warehousing principles, database design, and data modeling techniques (both relational and non-relational).
- Experience in developing and deploying machine learning models into production environments; familiarity with MLOps principles and tools is a strong advantage.
- Proficiency in building and automating dashboards and reports using tools like Looker, Power BI, Tableau, or Qlik Sense.
- Experience working with APIs for data ingestion and for leveraging AI services.
- Familiarity with connected vehicle data, dealer invoice data, automotive industry data, or customer experience metrics (e.g., NPS, CSAT) is a significant plus.
- Excellent analytical and problem-solving skills, with the ability to translate complex business problems into technical solutions and a keen attention to detail.
- Strong communication and interpersonal skills, with the ability to effectively collaborate with both technical and non-technical stakeholders.
- Self-motivated, proactive, and capable of working independently with minimal supervision, as well as effectively within a team in an agile environment.
- Knowledge of data governance and data security best practices, especially within a cloud context.
Please note that we currently run background checks as part of our recruitment process pending a successful interview.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Architecture BigQuery Chatbots Computer Science CX Dataflow Data governance Data pipelines Dataproc Data quality Data Warehousing ELT Engineering ETL GCP Google Cloud Looker Machine Learning Mathematics ML models MLOps NLP NumPy Pandas PhD Pipelines Power BI Python PyTorch Qlik Scikit-learn Security SQL Statistics Tableau TensorFlow Vertex AI
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