Fact Finders Pro
Senior Predictive Analytics Scientist (Volunteer-UnPaid)
Fact Finders Pro, Seattle, Washington, us, 98127
Senior Predictive Analytics Scientist (Volunteer-Unpaid)
We are looking for a Sr. Data Scientist with at least five years of experience in Python, developing basic-level prediction models.
Key Responsibilities
Collect data by analyzing business results or setting up and managing new studies.
Transform data into new formats suitable for analysis.
Create experimental frameworks to facilitate data collection.
Build tools to automate data collection.
Search large datasets to identify usable information.
Generate reports and presentations for business stakeholders.
Correlate similar data to uncover actionable insights, perform statistical analyses, and refine models.
Collaborate with software and business teams to build, integrate, and deliver algorithms within a modern SaaS platform.
Advance NLP applications to create innovative products and customer experiences, ranging from text understanding and classification to information extraction.
Develop end-to-end products from data exploration to feature generation, model construction, and deployment.
Own model design, implementation, and deployment, ensuring they deliver business impact.
Mentor team members and help grow the Data Science organization.
Guide design, architecture, tooling, and processes at the organization level.
Qualifications
Master's or advanced degree in Data Science, Computer Science, Statistics, or a related field.
Minimum of five years of experience in data exploration, cleaning, analysis, visualization, and mining.
At least six months to one year of LLM experience in projects.
Proven experience with Python for endorsing basic-level prediction models.
Deep understanding of machine learning and deep learning algorithms.
Knowledge of key quantitative fields: Natural Language Processing, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.
Statistical and data science programming skills, including Python and R.
SQL expertise for data extraction, transformation, and analysis.
Experience in Big Data, search, NLP, and chatbot technologies such as Elasticsearch and Solr.
Familiarity with deep learning tools such as TensorFlow, Keras, MXNet, or H2O (preferred).
Experience deploying NLP solutions in a commercial environment.
Extensive experience with Microsoft Azure, including machine learning certification.
Experience with Azure Machine Learning pipelines.
Knowledge of Agile methodologies and related project management tools (Jira, Azure DevOps, etc.).
Publicly available AI-related projects on GitHub.
#J-18808-Ljbffr
Key Responsibilities
Collect data by analyzing business results or setting up and managing new studies.
Transform data into new formats suitable for analysis.
Create experimental frameworks to facilitate data collection.
Build tools to automate data collection.
Search large datasets to identify usable information.
Generate reports and presentations for business stakeholders.
Correlate similar data to uncover actionable insights, perform statistical analyses, and refine models.
Collaborate with software and business teams to build, integrate, and deliver algorithms within a modern SaaS platform.
Advance NLP applications to create innovative products and customer experiences, ranging from text understanding and classification to information extraction.
Develop end-to-end products from data exploration to feature generation, model construction, and deployment.
Own model design, implementation, and deployment, ensuring they deliver business impact.
Mentor team members and help grow the Data Science organization.
Guide design, architecture, tooling, and processes at the organization level.
Qualifications
Master's or advanced degree in Data Science, Computer Science, Statistics, or a related field.
Minimum of five years of experience in data exploration, cleaning, analysis, visualization, and mining.
At least six months to one year of LLM experience in projects.
Proven experience with Python for endorsing basic-level prediction models.
Deep understanding of machine learning and deep learning algorithms.
Knowledge of key quantitative fields: Natural Language Processing, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.
Statistical and data science programming skills, including Python and R.
SQL expertise for data extraction, transformation, and analysis.
Experience in Big Data, search, NLP, and chatbot technologies such as Elasticsearch and Solr.
Familiarity with deep learning tools such as TensorFlow, Keras, MXNet, or H2O (preferred).
Experience deploying NLP solutions in a commercial environment.
Extensive experience with Microsoft Azure, including machine learning certification.
Experience with Azure Machine Learning pipelines.
Knowledge of Agile methodologies and related project management tools (Jira, Azure DevOps, etc.).
Publicly available AI-related projects on GitHub.
#J-18808-Ljbffr