What does a successful Senior Data Scientist do at Fiserv?
As a Senior Data Scientist within Data Commerce Solutions, you will design and develop products and solutions to drive innovation. You will leverage Artificial Intelligence, Machine Learning and Deep Learning models in addition to other statistical techniques to target specific business objectives and create other business opportunities.
What you will do:
- You will design and develop inventive products & solutions to drive innovation leveraging AI/ML/DL models to target specific business objectives and create other business opportunities.
- Design and develop custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines
- Utilize LangChain / LlamaIndex for advanced language processing tasks. Perform fine-tuning of models and work with Parameter-Efficient Fine-Tuning (PEFT), RAG, and Agentic AI Frameworks
- Work in a highly collaborative, team environment, and collaborating with multiple stakeholders including business, product development, architecture and engineering teams to develop, deploy , monitor and maintain ML models.
- Assist in the communication of insights and the implementation of impactful data science solutions across the organization.
What you will need to have:
- Bachelor’s degree in Statistics, Data Science, Computer Science, Operations Research or related field.
- 5+ years of hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, RAG, and NLP.
- 5+ years of experience formulating research or business problems, designing, experimenting, implementing and communicating solutions.
- Proficiency in tokenization and embeddings, as well as experience creating models, improving model training and tuning, and deploying Large Language Model architectures based on LLaMA, BERT, or Transformer-based models.
- Hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch and Agentic AI frameworks.
- Strong knowledge of statistical data analysis and machine learning techniques (e.g., SVM, regression, classification, clustering, time series) and familiarity with financial analytics, time series econometrics, payment processing and marketing strategies.
- Working knowledge of Hadoop, Hive, Impala, RDBMS, SQL, Snowflake, Vertica & RDBMS, or NoSQL Databases
- Familiarity with data platforms and applications such as Azure ML, Databricks ML, AWS Sage maker and experience contributing to GitHub and open-source initiatives.
What would be great to have:
- Master’s degree, PhD, or equivalent practical experience, in Computer Science, or related technical field.
- Publication record in relevant conferences and/or participation in Kaggle competitions.
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