Who are we
Amdocs helps those who build the future to make it amazing. With our market-leading portfolio of software products and services, we unlock our customers innovative potential, empowering them to provide next-generation communication and media experiences for both the individual end user and enterprise customers. Our employees around the globe are here to accelerate service providers migration to the cloud, enable them to differentiate in the 5G era, and digitalize and automate their operations. Listed on the NASDAQ Global Select Market, Amdocs had revenue of $5.00 billion in fiscal 2024. For more information, visit www.amdocs.com
Location: Pune
Experience: 6 to 10 Years
Must-Have Skills:
- Generative AI
- Python
- RAG (Retrieval-Augmented Generation)
- LLM / NLP
- EDA (Exploratory Data Analysis)
- Cloud Platforms (AWS, Azure, GCP)
- Transformers
- Explainable AI
- Deep Learning
Desired Background
- At least 4+ years of relevant experience and track record in Data Science: Machine Learning, Deep Learning and Statistical Data Analysis.
- MSc or PhD degree in CS or Mathematics, Bioinformatics, Statistics, Engineering, Physics or similar discipline.
- Strong hands-on experience in Python with the focus being on statistical algorithms development and GenAI practices.
- Experience with data science libraries such as: sklearn, pandas, numpy, pytorch/tensorflow
- Experience with GenAI concepts (RAG, LLM) and Agentical development: from conversional to autonomous agents
- Team player, able to work in collaboration with subject matter experts, with ability to clearly present and communicate findings.
- Proven ability to build and deliver data solutions in a short time frame.
- Experience with Azure, docker, and development methodologies - an advantage
- Proven experiences in productions and DevOPS practices
nd find the right answers.
Qualifications
- Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 1 - 2 years of experience in quantitative analytics or data modeling
- Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
- Fluency in a programming language (Python, C,C++, Java, SQL)
- Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)