The scientist will work on a team with deep expertise in computational biology, data science, genomics, and pharma/biotech partnerships – with the unified goal of deriving maximal value from Caris’ data for external and internal research efforts to advance cancer care.

If the candidate does not have a background in Actuarial science, the candidate should have 4+ years of industry experience building and analyzing machine learning models and should hold a graduate degree in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics, Physics, Mathematics, Economics or Engineering.

10 years of experience in data engineering, data architecture, BI & Analytics, and/or Data Science. Execute the HW Analytics Strategy that includes building a modern Unified Data Warehouse, expanded Self-Service, and Data Science capabilities.

We work alongside product teams across MI ES on break-through ideas using tools and techniques spanning the entire spectrum of Data Science, Statistics, Machine Learning, Deep Learning, NLP, Gen AI, Operations Research, Data and Machine Learning Engineering.

5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.

Work Week: Standard (M-F equal number of hours per day) Posting Position Title: Research Specialist University Job Title: Data Scientist Preferred Education, Experience and Skills: Ph. D. in a quantitative field like Economics, Physics, Statistics, Mathematics, Data Science, Engineering, Health Policy or related fields.

The PositionThe Science Engagement Division at the Adler Planetarium (Adler) is seeking candidates for a Postdoctoral Fellowship position in the field of Data Science, with an emphasis on Remote Sensing and Geospatial Analysis.

Studying Business Analytics, Data Engineering, Data Science, Computer Engineering, Electrical Engineer, or Computer Science. KEY QUALIFICATIONS: Python, SQL Data processing, ML experience Data Warehouse knowledge ETL pipeline knowledge Data Engineering Data Science Data Analytics, Data Mining PLEASE HAVE KNOWLEDGE OF ONE OR MORE OF THE FOLLOWING TECHNICAL SKILLS: Kubernetes, Tableau, PowerBi MongoDB Microsoft Cloud Services like Azure and AKS Snowflake SQL Server data platform Software development (including design, implementation, testing, and change management.

Fort Worth, TX company is seeking a Data Engineer to join their team for a contract opportunity. 3+ years of cloud development and data lake experience (prefer Microsoft Azure) including Azure EventHub, Azure Data Factory, Azure Functions, ADX, ASA, Azure Databricks, Azure DevOps, Azure Blob Storage, Azure Data Lake, Azure Power Apps and Power BI. Airline Industry Experience.

Current PhD - Data Science Internship - Summer 2025. If you're interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey.

YOUR SKILLS AND EXPERTISEBachelor’s degree in computer science, data science or a related field with five (5) or more years of working as a data engineer, ETL developer and/or data warehouse DBA.STANDOUT QUALIFICATIONS:Experience with Cloud-based data services and solutions (Azure Synapse / Data Lake, AWS RedShift, Snowflake, GCP Big Query)Experience partnering with Analytics and Data Science teams in building out production grade GenAI/ML solutions.

Data Internship We offer internships in different data roles including: Data Analyst Intern Data Scientist Intern Business Analytics Your Experience and Qualifications Current student enrolled in an accredited 4-year college or university in Data Science, Information Management, Computer Science, Computer Engineering, or a related field.

Prior work experience as a data analyst or statistical programmer, quantitative epidemiologist or similar role, preferably in public health, biostatistics, epidemiology or similar environment, preferably in an academic or quasi-academic setting is strongly preferred.

Responsibilities:Enterprise Data Engineering Delivery:Oversee the design, development, and management of scalable and reliable data engineering solutions that support data products deployment for use in advanced analytics, data science, and AI initiatives.

This include applying data science and technology skillsets when working with large-scale financial institutions, financial technology ("fintech") organizations, and other money service businesses.