Principal Data Science Engineer at Jobgether

, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Dec, 25

Salary

200000.0

Posted On

24 Sep, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Engineering, Python, Java, Cloud Platforms, Data Strategy, Feature Engineering, Model Production, Stakeholder Collaboration, Technical Leadership, Analytical Thinking, Problem Solving, Data Pipelines, APIs, Security Best Practices, Mentorship

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Data Science Engineer in Georgia (USA). This is a senior, high-impact role for an experienced data science professional eager to influence a fast-growing team. You will work across the full machine learning lifecycle, from data ingestion and feature engineering to model production and deployment, helping to build a data-rich platform that matches, optimizes, and retains skilled talent. The position offers autonomy, exposure to cutting-edge technologies, and the chance to make meaningful contributions to a mission-driven organization. You will collaborate with cross-functional teams, contribute to data strategy, and directly impact product innovation and customer value. This is an opportunity to grow as both a technical leader and strategic thinker in a startup-like environment with large-scale impact. Accountabilities Design, build, and deploy full-stack machine learning solutions supporting talent matching, retention, and workforce optimization. Develop and maintain data pipelines, feature engineering processes, and production-grade ML models. Partner with stakeholders to define and execute a long-term data strategy aligned with business goals. Analyze market and user behavior data to inform new feature development and ROI measurement. Ensure security best practices and compliance around sensitive data, including PII. Contribute to the architecture of client-facing algorithms, APIs, and core product features. Provide technical leadership and mentorship within the data science and engineering teams. 10+ years of experience building and shipping production-grade data products. Strong proficiency in Python and Java, with experience across cloud platforms (AWS, GCP, Azure). Hands-on experience across the full machine learning lifecycle: EDA, modeling, productionization, monitoring. Ability to flex between pure data science and full engineering execution as business needs demand. Experience in early-stage startup environments or high-growth teams. Strong problem-solving skills, analytical thinking, and attention to detail. Deep alignment with mission-driven work and values-centered leadership. Preferred Qualifications: Experience at major technology companies (e.g., Amazon, Google, Meta, Apple, Microsoft, Netflix). Prior involvement in large-scale talent or workforce analytics platforms. Familiarity with client operations, APIs, and full-stack engineering approaches. Competitive compensation: $150,000–$200,000 per year. Comprehensive medical, dental, and vision coverage. Paid time off and flexible remote work policy. Stock participation or equity plans. Opportunity to shape early-stage product strategy and drive large-scale 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

Design, build, and deploy full-stack machine learning solutions to support talent matching and workforce optimization. Collaborate with cross-functional teams to define and execute a long-term data strategy aligned with business goals.