Sr Data Scientist PhD with GenAI & NLP - Hybrid on site
Sr Data Scientist PhD with GenAI & NLP - Hybrid on site
Posted on :
06-05-2025
Employer Active
1 Vacancy
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Share
Send me jobs like this
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Jobs by Experience
8-10years
Monthly Salary
$ 75 - 85
Vacancy
1 Vacancy
Posted on :
06-05-2025
Job Description
Sr Data Scientist PhD with GenAI & NLP Hybrid on site
Minimum Qualifications:
- Work or educational background in one or more of the following areas: machine learning computational linguistics deep learning ratification intelligence data science and/or data analytic generative AI symbolic AI causal AI operations research computer science Mathematics business analytics or knowledge management.
- 812 years of demonstrated experience programming with R/Python Linux and Spark in AWS cloud environment or knowledge and algorithmic design experience in Python (3 years)
- Proficient with Amazon AWS Sagemaker Jupyter Notebook and Python Scikit Deep Learning Machine Learning tools such as TensorFlow
- Experience with image processing models such as Coco CLIP ResNet or comparable models
- Demonstrated experience with machine learning techniques including natural language processing and Large language Models (GPTv4o1 o3 OpenAI APIs Llama Claude etc).
- Experience developing AI agents and development proficiency using agentic programming
- Proficient in Natural language processing (NLP) and Natural language generation (NLG) including prior projects in any of the following categories: top modeling of text sentiment analysis of text part of speech tagging Name Entity Recognition (NER) Bag of Words text extraction
- Experience building and working with any of these components: Vector DB BERT RoBERTa (or comparable tools) Spacy LLM and GenAI tools. Experience with LoRA LangChain RAG LLM Fine Tuning and PEFT Knowledge Graphs.
- Strong skills in developing GraphRAG Chain of Thought (CoT) Tree of Thought (ToT) Reinforcement learning and AI development architectures with HumanintheLoop (HITL
- Demonstrated experience with SQL and any relational database technologies such as Oracle PostgreSQL MySQL RDS Redshift Hadoop EMR Hive etc.
- Demonstrated experience processing structured and unstructured data sources data cleansing data normalization and prep for analysis
- Demonstrated experience with code repositories and build/deployment pipelines specifically Jenkins and/or Git/GitHub/GitLab.
- Demonstrated experience using Tableau or Kibana Quicksights or other similar data visualizations tools.
- Very comfortable working with ambiguity (e.g. imperfect data loosely defined concepts ideas or goals)
Qualifications & Requirements
- Education: MS in Computer Science Statistics Math Engineering or related field PhD preferred.
- 3 years of relevant experience in building large scale machine learning or deep learning models and/or systems
- 1 year of experience specifically with deep learning (e.g. CNN RNN LSTM)
- 1 year of experience building NLP and NLG tools.
- Experience with wide range of LLMs (Llama Claude OpenAI Cohere etc.) LoRA LangChain RAG LLM Fine Tuning and PEFT are preferred.
- Demonstrated skills with Jupyter Notebook AWS Sagemaker or Domino Datalab or comparable environments
- Passion for solving complex data problems and generating crossfunctional solutions in a fastpaced environment
- Knowledge in Python and SQL object oriented programming service oriented architectures
- Strong scripting skills with Shell script and SQL
- Strong coding skills and experience with Python (including SciPy NumPy and/or PySpark) and/or Scala.
- Knowledge and implementation experience with NLP techniques (topic modeling bag of words text classification TF/IDF Sentiment analysis) and NLP technologies such as Python NLTK or Spacy or comparable technologies
- Knowledge and implementation experience with statistical and machine learning models (regression classification clustering graph models etc.)
Preferred Qualifications
- Hands on experience building models with deep learning frameworks like Tensorflow Keras Caffe PyTorch Theano H2O or similar
- Experience with LLM Agents Agentic programming
- Experience with search architecture (for instance: Solr ElasticSearch AWS OpenSearch)
- Experience with building querying ontologies such as Zeno OWL RDF SparQL or comparable are preferred
- Knowledge & experience with microservices service mesh API development and test automation are preferred
- Demonstrated experience using Docker Kubernetes and/or other similar container frameworks are preferred
Additional Job Qualifications:
- Ability to translate business ideas into analytics models that have major business impact.
- Demonstrated experience working with multiple stakeholders.
- Demonstrated communication skills e.g. explaining complex technical issues to more junior data scientists in graphical verbal or written formats.
- Demonstrated experience developing tested reusable and reproducible work.
Requirements
Interview Process/# of Rounds:
Interview Process/# of Rounds:
- Direct manager contact
- 2 rounds
Sr Data Scientist GenAI & NLP Proficient with AI Agents in NLP & NLG Qualifications Minimum Qualifications: Work or educational background in one or more of the following areas: machine learning, computational linguistics, deep learning, ratification intelligence, data science and/or data analytic, generative AI, symbolic AI, causal AI, operations research, computer science, Mathematics, business analytics, or knowledge management. Demonstrated experience programming with R/Python, Linux, and Spark in AWS cloud environment, or knowledge and algorithmic design experience in Python (3+ years) Proficient with Amazon AWS Sagemaker, Jupyter Notebook and Python Scikit, Deep Learning, Machine Learning tools such as TensorFlow Experience with image processing models such as Coco, CLIP, ResNet or comparable models Demonstrated experience with machine learning techniques including natural language processing, and Large language Models (GPTv4-o1, o3, OpenAI APIs, Llama, Claude, etc). Experience developing AI agents and development proficiency using agentic programming Proficient in Natural language processing (NLP) and Natural language generation (NLG) including prior projects in any of the following categories: top modeling of text, sentiment analysis of text, part of speech tagging, Name Entity Recognition (NER), Bag of Words, text extraction Experience building and working with any of these components: Vector DB, BERT, RoBERTa (or comparable tools), Spacy, LLM and GenAI tools. Experience with LoRA, LangChain, RAG, LLM Fine Tuning and PEFT, Knowledge Graphs. Strong skills in developing GraphRAG, Chain of Thought (CoT), Tree of Thought (ToT), Reinforcement learning and AI development architectures with Human-in-the-Loop (HITL Demonstrated experience with SQL and any relational database technologies, such as Oracle, PostgreSQL, MySQL, RDS, Redshift, Hadoop EMR, Hive, etc. Demonstrated experience processing structured and unstructured data sources, data cleansing, data normalization and prep for analysis Demonstrated experience with code repositories and build/deployment pipelines, specifically Jenkins and/or Git/GitHub/GitLab. Demonstrated experience using Tableau, or Kibana, Quicksights or other similar data visualizations tools. Very comfortable working with ambiguity (e.g. imperfect data, loosely defined concepts, ideas, or goals) Qualifications & Requirements Education: MS in Computer Science, Statistics, Math, Engineering, or related field, PhD preferred. 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems 1+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM) 1+ year of experience building NLP and NLG tools. Experience with wide range of LLMs (Llama, Claude, OpenAI, Cohere, etc.), LoRA, LangChain, RAG, LLM Fine Tuning and PEFT are preferred. Demonstrated skills with Jupyter Notebook, AWS Sagemaker, or Domino Datalab or comparable environments Passion for solving complex data problems and generating cross-functional solutions in a fast-paced environment Knowledge in Python and SQL, object oriented programming, service oriented architectures Strong scripting skills with Shell script and SQL Strong coding skills and experience with Python (including SciPy, NumPy, and/or PySpark) and/or Scala. Knowledge and implementation experience with NLP techniques (topic modeling, bag of words, text classification, TF/IDF, Sentiment analysis) and NLP technologies such as Python NLTK, or Spacy or comparable technologies Knowledge and implementation experience with statistical and machine learning models (regression, classification, clustering, graph models, etc.) Preferred Qualifications Hands on experience building models with deep learning frameworks like Tensorflow, Keras, Caffe, PyTorch, Theano, H2O, or similar Experience with LLM Agents, Agentic programming Experience with search architecture (for instance: Solr, ElasticSearch, AWS OpenSearch) Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL or comparable are preferred Knowledge & experience with microservices, service mesh, API development and test automation are preferred Demonstrated experience using Docker, Kubernetes, and/or other similar container frameworks are preferred Additional Job Qualifications: Ability to translate business ideas into analytics models that have major business impact. Demonstrated experience working with multiple stakeholders. Demonstrated communication skills, e.g. explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats. Demonstrated experience developing tested, reusable and reproducible work.
Education
Master's and PHD REQUIRED
Employment Type
Full Time
Company Industry
Key Skills
Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.
