Full Stack Data Scientist (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

11 Jan, 26

Salary

140000.0

Posted On

13 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, AI, SQL, Python, AWS, dbt, Snowflake, Agile, Model Deployment, Data Pipelines, Feature Engineering, Collaboration, Problem Solving, AI Ethics, Social Impact

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Full Stack Data Scientist in the United States. The Full Stack Data Scientist will be instrumental in driving AI and machine learning initiatives that power high-impact social good solutions. This role combines deep analytical skills with engineering expertise to build, deploy, and maintain production-ready models and data pipelines. You will collaborate closely with Product and Engineering teams in a distributed Agile environment, contributing to AI-driven features that enhance decision-making and optimize outcomes. The position offers opportunities to influence model architecture, implement scalable solutions, and mentor peers on best practices while maintaining rigorous standards for reliability, security, and ethics. The role provides a chance to directly impact non-profits, public sector organizations, and philanthropic initiatives, helping maximize their positive effect on society. Accountabilities: Own the end-to-end lifecycle of predictive and generative models, including problem definition, solution design, feature engineering, modeling, validation, deployment, and monitoring. Build and maintain production-ready data pipelines using SQL, dbt, and Snowflake. Develop models in Python and deploy them in cloud environments, including AWS services such as Bedrock, SageMaker, and Lambda. Collaborate with Product and Engineering teams on cross-functional projects in a remote and distributed Agile environment. Monitor and continuously improve model performance in production, ensuring reliability, scalability, and ethical AI practices. Translate analytical insights into actionable business outcomes for social impact initiatives. 3+ years of experience in Data Science on a Product team or related role; Agile experience preferred. Hands-on experience with AWS Bedrock, SageMaker, or other LLM providers. Strong proficiency in SQL and Python; experience with dbt and Snowflake. Knowledge of data governance, monitoring, and production deployment practices. Experience working on remote or distributed teams. Familiarity with AI ethics and responsible AI practices. Strong problem-solving, communication, and collaboration skills with a commitment to social impact. Competitive US-based salary range: $85,000 – $140,000. Comprehensive healthcare and wellness programs. Paid time off and parental leave. Opportunities for professional development, training, and growth. Remote and flexible work options to support work-life balance. Inclusive and equitable workplace culture focused on meaningful social impact. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

Own the end-to-end lifecycle of predictive and generative models, including problem definition, solution design, feature engineering, modeling, validation, deployment, and monitoring. Collaborate closely with Product and Engineering teams to enhance decision-making and optimize outcomes for social good initiatives.