Data Scientist

October 26

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Data Society

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Data analytics • E-learning • Data science • Corporate training • Executive training

11 - 50

Description

• The Data Scientist is responsible for combining their expert knowledge in statistical analysis, data mining, data engineering, and artificial intelligence to build complex end-to-end business analytics, artificial intelligence, and IT solutions. • This is a customer-facing role within a cross-functional team so the ability to manage timelines, work both autonomously and collaboratively, and communicate effectively are a must. • Ability to build a full data pipeline from data ingestion to processing/transformation to load to visualization and analysis. • Strong working experience with descriptive and predictive data mining tasks as well as key algorithms including ML and NLP-based learning techniques. • Understand and develop quantitative simulations and models as part of larger decision systems. • Develop and build modern AI-based applications using LLMs, RAG, and modern cloud tools. • Identify and incorporate new data sources into centralized, interoperable data stores via a variety of techniques including web scraping, APIs, secure file transfer, etc. • Perform sentiment analysis, topic modeling, and text classification to understand opinions, identify trends, and extract key themes. • Identify and present insights, trends, and problems through complex big data analysis to both technical and non-technical audiences. • Collaborate with team members across the company to support client capture, proposal writing, and sales development. • Support the technology team in staying current in emerging tools and techniques in machine learning, statistical modeling, and analytics. • Create clear and compelling visualizations to communicate data-driven insights to stakeholders.

Requirements

• Advanced Degree in Statistics, Applied Mathematics, Data Science, Computer Science, Operations Research or other closely related quantitative or mathematical disciplines. • 5+ years of relevant data science and analytics experience. • Expertise with SQL, R and Python, and other scripting and statistical programming languages. • Experience with use of large cross-sectional and time series data, with a strong foundation in statistical concepts. • Proficient in analyzing textual data using the latest NLP techniques. • Experienced in building RAG powered LLM applications. • Skilled in developing and maintaining data pipelines and ETL processes for data preparation. • Proficient in leveraging AWS tools for data integration, orchestration, and machine learning development and deployment. • Familiarity with analytic tools such as PowerBI and Tableau is a plus. • Excellent communication skills with the ability to work independently and collaboratively across functions, demonstrating strong problem-solving and critical thinking abilities.

Benefits

• Unlimited PTO • paid holidays in 2025 • Healthcare • 401k • Metro Transit subsidy • Paid Parental Leave • Paid Disability