GPT jobs

About Us:

Datacor is the leading provider of software solutions, including ERP, CRM, Asset Tracking, Simulation and Formulation, to the process manufacturing space. We are on a mission to better equip the industry with software solutions and move it forward by building thoughtful, intuitive products that solve our customers’ most difficult problems.

We are passionate about serving our customers and helping them use data as a competitive advantage. Our customers make products that extend and sustain lives by sanitizing, fertilizing, beautifying, cleaning, and recycling the world we live in. We at Datacor help our customers make those products you use every day more safely, cost effectively and more efficiently through our technology platforms and applications.

The Role: 

As a Data Scientist Intern, you will be tasked with key aspects of data science and data analytics development, guided by experienced engineers. You’ll be tasked with spearheading efforts to design and execute on experiments that solve a pre-defined goal. You’ll help discover new ways to look at the information being collected and assist in designing solutions that address customer needs, including automated computer vision and forecasting systems to drive revenue and decrease costs at our customers. You should be comfortable with time-series analysis and have a strong knowledge of machine learning methods.

Responsibilities:

• Clean large, complex data sets and customer metadata, identifying the right tool out of the toolkit to achieve a desired outcome for the data
• Develop algorithms related to computer vision, forecasting and unsupervised learning methods
• Implement existing Large Language Models such as GPT, LLaMA, etc.
• Perform data analysis on user behavior to inform product features
• Partner with cross-functional teams including Product, Engineering, Customer Success, and Sales to assist in various efforts around data analysis. Develop strong relationships with team members and ask the right questions to solicit help and feedback when appropriate
• Maintain deep and up-to-date knowledge of the data warehouse; troubleshoot data inconsistencies
• Translate business needs into analytical tasks, documenting and presenting results to both technical and non-technical audiences
• Interpret results using a variety of techniques, ranging from simple exploratory data analysis to statistical modeling
  
• Own discrete portions of the data science pipeline, including but not limited to data cleaning procedures, exploratory data analysis, modeling and visualization, and feature-selection methodologies
• With guidance, interview and gather feedback from customers and internal parties on data problems. Work with other team members to devise solutions to these problems as appropriate.
  

Qualifications:

• Currently enrolled in a Master’s program or higher with a strong academic record required in one of the following: Statistics, Computer Science, Operations Research, Economics, Physics, or Engineering
• Strong command of machine learning methodologies; able to articulate key concepts and implement in working code
• Prior experience with owning small to medium-scale data science projects and presenting results to key stakeholders; able to logically support modeling approaches and cite benefits and drawbacks of alternatives to the business
• Prior experience with auditing models and performing quality control checks on other team members’ code and methods
• Prior experience with project scoping, defining deliverables, timelines, etc. as well as communicating end-results with formal documentation
• Complex SQL queries background with an emphasis on efficiency of execution time
• Experience with R or Python; has worked with productionalized code
• Demonstrated ability to maintain performance level in a fast-paced environment with changing priorities and deadlines
• A self-starter with the ability to work independently and within a team
• Experience in a professional environment, including prior internship experience is preferred 

This is a remote internship with potential travel, depending on location, schedule, and business needs.