Data Scientists Modeling
Job DescriptionJob DescriptionTitle: Data Scientists ModelingLocation: Dearborn, MI (Hybrid)Job Type: Long Term Contract
Job Description:Acquire deep understanding of the business problems and translate them into appropriate business solutions Act as full stack data scientist to develop and deliver advanced analytics models, including classification, time series, LLM, and more Collaborate internally and externally to identify new and novel data sources and explore their potential use in developing actionable business results Work independently with minimal guidance, taking ownership of projects and delivering results Foster a collaborative team environment, showing highest respect for team members and their contributions Demonstrate curiosity about data, seeking to understand its underlying patterns and relationships Ensure high-quality data and solutions throughout the development process Communicate analytical results effectively to various audiencesSkills Required:
Generative AI, Predictive modelling & Data exploration.Skills :
Experience in Generative AI Experience in legal or regulatory domains 5+ years of experience in data science and analysis, including full-time work and research/academia experience Certifications in Google Cloud Platform (GCP) or other cloud platformsExperience Required:
3+ years of experience in AI/ML, preferably with some experience in Generative AI Strong skills in data acquisition, algorithm design, model development, and refinement Experience with big data technologies, cloud-based data platforms (e.g., GCP, AWS), and business intelligence tools (e.g., Qlik Sense, Looker, Streamlit, Dash)Experience :
Excellent oral, written, and interpersonal communication skills Ability to work collaboratively and drive results in a fast-paced environmentEducation Required:
M.S. in Data Science, Business Analytics, Machine Learning, Computer Science or a related quantitative fieldEducation :
Ph.D. in Data Science, Business Analytics, Machine Learning, Computer Science or a related quantitative field