Associate Data Scientist
Associate Data Scientist
Philips7-9 Years
- Posted 50 minutes ago
- Be among the first 10 applicants
Job Description
Job Title
Associate Data Scientist
Job Description
Job Responsibilities:
Someone who can design, build, and fine-tune Generative AI models (LLMs, vision-language models, diffusion models) for product use cases
Hands on expertise in Large Language Models and prompt engineering
RAG architectures, vector databases, embeddings
Experiment tracking tools (MLflow, Weights & Biases)
Traditional ML/DL techniques
Work with structured and unstructured datasets (images, text)
Collaborate with engineering teams to integrate AI models into production systems and embedded/edge environments
Minimum Required Education
Bachelor's / Master's Degree in Information Management, Information Systems, Computer Science, Data Analytics, Data Science or equivalent.
Minimum Required Experience
Minimum 7 years of experience with Bachelor's OR Minimum 5 years of experience with Master's in areas such as Data Analytics, Data Modeling or equivalent.
Preferred Skills
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.
Onsite roles require full-time presence in the company's facilities.
Field roles are most effectively done outside of the company's main facilities, generally at the customers or suppliers locations.
Indicate if this role is an office/field/onsite role.
About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
Associate Data Scientist
Job Description
Job Responsibilities:
Someone who can design, build, and fine-tune Generative AI models (LLMs, vision-language models, diffusion models) for product use cases
Hands on expertise in Large Language Models and prompt engineering
RAG architectures, vector databases, embeddings
Experiment tracking tools (MLflow, Weights & Biases)
Traditional ML/DL techniques
Work with structured and unstructured datasets (images, text)
Collaborate with engineering teams to integrate AI models into production systems and embedded/edge environments
Minimum Required Education
Bachelor's / Master's Degree in Information Management, Information Systems, Computer Science, Data Analytics, Data Science or equivalent.
Minimum Required Experience
Minimum 7 years of experience with Bachelor's OR Minimum 5 years of experience with Master's in areas such as Data Analytics, Data Modeling or equivalent.
Preferred Skills
- Data Science
- Data Analysis & Interpretation
- Data Designing
- Python
- GenAI frameworks(LangChain, LangGraph)
- Vector Databases
- Machine Learning Engineering Fundamentals
- Statistical Methods
- Statistical Programming Software
- Research & Analysis
- Structured Query Language (SQL)
- Regulatory Compliance
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.
Onsite roles require full-time presence in the company's facilities.
Field roles are most effectively done outside of the company's main facilities, generally at the customers or suppliers locations.
Indicate if this role is an office/field/onsite role.
About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
- Learn more about our business.
- Discover our rich and exciting history.
- Learn more about our purpose.
More Info
Key Skills
Statistical Programming Software
embeddings
Data Analysis Interpretation
Structured Query Language SQL
vision-language models
vector databases
MLflow
Traditional ML
Data Designing
LangGraph
Generative AI models
Large Language Models
RAG architectures
Weights Biases
LangChain
LLMs
Machine Learning Engineering Fundamentals
Statistical Methods
prompt engineering
GenAI frameworks
diffusion models
About Company
Skills:
SAS, Sql, Python, R, AI/ML and advanced analytics, Clinical Trial Design, Drug development endpoints, Biomarkers data interpretation
Skills:
thoughtspot , Sql, Tensorflow, Pytorch, XGBoost, Databricks, Python, Amazon Web Services, Machine Learning, Qlik Sense, Alteryx, Hadoop, Etl Tools, Tableau, Azure, Google Cloud, Deep Learning, Scikit-learn
Skills:
Generative AI, Ranking systems, Developing and fine-tuning LLMs, Data-centric machine learning, AI-driven personalization, AI agents, Search relevance
Skills:
causal inference , Time Series Analysis, Hypothesis Testing, Recommender Systems, Azure Synapse Analytics, Databricks, Clustering, Azure Machine Learning, uplift modeling, lifetime value modeling, experimentation design, Classification, Azure Data Lake Storage, Regression, dashboard development, personalization algorithms, statistical methods
Skills:
Logistic Regression, Decision Tree, Linear Regression, Svm, scrapy, Sql, Pca, Random Forest, Nosql, Neural Network, Numpy, Pandas, Gcp, Spark, Azure, Python, AWS, scikit-learn, K-mean Clustering, R, scapy, BERT