Sr Data Scientist With LLMS
20 days ago
Carteret
Job Description This is a remote position. SR DATA SCIENTIST Duration: 12+ months What problem are we trying to solve: • The Senior Data Scientist will support our organization's data-driven initiatives by providing insights, developing predictive models, and driving data-centric decision-making across various business domains., • This role will act as the primary contact for advanced analytics projects, collaborating with cross-functional teams to extract valuable insights from complex datasets. Tech Stack • Embedded within product development teams. Responsibilities include: • Building and evaluating models., • Refining business-defined measures and metrics., • Supporting dynamic and creative approaches to data science., • Tech environment: AWS, Python preferred (other languages possible), avoiding excessive language spread. Hard Requirements: Technical Skills: Common Technologies/Tools: Programming Languages: Python, R, SQL Data Visualization Tools: Tableau, Power BI, DataDog Version Control Systems: Git, GitHub Project Management Tools: Jira, Confluence Cloud Platforms: AWS, Azure, Google Cloud Platform Data Warehousing: Redshift, BigQuery, Snowflake Soft Skills: • Advanced Statistical Analysis and Modeling, • Proficiency in statistical methods and machine learning algorithms., • Experience with predictive modeling and forecasting. Programming and Scripting: • Strong programming skills in Python or R., • Proficient in SQL for database querying., • Data Visualization and Storytelling, • Ability to create compelling visualizations to communicate insights., • Experience with data visualization tools like Tableau, Power BI, or DataDog., • Problem-Solving and Critical Thinking, • Strong analytical skills to tackle complex business challenges., • Ability to think strategically and provide data-driven recommendations., • Communication and Collaboration, • Excellent verbal and written communication skills., • Ability to work effectively in cross-functional teams., • Knowledge of Software Development Lifecycle ( SDLC ), • Understanding of best practices in software and data pipeline development. Requirements • 60%+ of this gig is building LLMs - and doing so from scratch. Hence the need for DS with, a) this expertise; and, b) have done so in a commercial setting [as opposed to academia when in a Research capacity]., • They need to have built the LLMs, built the pipelines, deployed 'em and managed/monitored 'em., • These LLMs must have had a quantifiable business impact which is demonstrable on the resume and in an interview., • Finally.....as for alGORITHM/MLexpertise, we need to find folks with the following: "... knowledge of statistics and have developed ML models like Random Forst, XGboost, Regression, and other classification and regression forecasting... " In summary....these DS roles are very similar to those of Toyota Connected. Guys who can do it all - interface and gather Clients from stakeholders, build the models, deploy, manage and utilize. They won't get much in the way of technical or business direction - they will be self-sufficient and the ones who drive the insights, "Look what I found.... " bus. They CANNOT be the types who just sit at their desk crunching numbers, publishing reports and onto the next. They need to be on the front foot and pushing the boundaries.