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Rockstar

Senior Data Scientist

Posted 5 Hours Ago
Remote
Hiring Remotely in United States
115K-140K Annually
Senior level
Remote
Hiring Remotely in United States
115K-140K Annually
Senior level
Lead ML/NLP work across recommender systems, taxonomies, and agentic AI solutions. Prototype models, advise on data science strategy, mentor teammates, and deliver production-ready, well-documented ML pipelines and insights.
The summary above was generated by AI

Rockstar is recruiting for a mission-driven AI company that is dedicated to resolving economic inequality by helping more people access better jobs faster and more affordably, with a special focus on those facing barriers to opportunity. The company's AI-powered platform brings efficiency and insight to workforce development, replacing outdated systems and unlocking human potential at scale. They are a dynamic, high-performing team motivated by meaningful impact.

Join the Data team!

High velocity, high intensity, high trust, high bar, high impact, and a will to win.

If those words resonate deeply, this could be a next career move. They are seeking someone who leads with humility, pursues audacious goals, and is motivated by meaningful impact on people and the world.

The core mission is to help more people get to better jobs faster and cheaper, with a specific focus on those facing barriers to opportunity. The work helps resolve the growing issue of economic inequality, ensuring that no one is left behind in the future of work. The AI-powered platform brings efficiency and insight to workforce development, replacing outdated systems and unlocking human potential at scale.

Ready to make an impact? Apply today.

Important note: Data shows that men typically apply when meeting 3/10 requirements, while women often wait until it's 10/10. They encourage you to apply if you see a strong (not necessarily perfect) fit.

Your Role

They are seeking a Data Scientist to join the team. Do you love working in machine learning pipelines with big data from day one? Do you have hands-on experience in state-of-the-art NLP (e.g., transformers, BERT, few-shot learning, fine-tuning) and information retrieval (e.g., vector-based semantic search, reranking, hybrid search)? Do you want to continue to work at the frontier of advanced ML and NLP, at a mission-driven startup where they love what they do? If this sounds like you, this might be a dream job!

What You’ll Own

- Recommender Systems: Ensuring the product makes high-quality recommendations to both job seekers (as a “GPS” for their careers) and employers (as a “talent radar”).

- Taxonomies: Using data and AI to model and make sense of the evolving landscape of skills, occupations, and careers in a changing labor market.

- Agentic AI Solutions: Prototyping and evaluating new AI-powered functions for job seekers, employers, and case workers.

- Data Science Strategy: You will serve as an advisor and expert on strategy and roadmap decisions, evaluate major developments in the field, and ensure they are using state-of-the-art techniques.

- Mentorship/Leadership: You are a dedicated mentor and can serve as tech lead, assisting with the quality, rigor, and acceleration of projects and tasks.

Required Experience

- 5+ years of combined experience in industry and/or graduate-level research.

- Proficiency training and evaluating ML and NLP models using both structured and unstructured data with reproducible results.

- Expert-level programming and software engineering skills and a track record of delivering re-usable and well-documented code.

- Practical knowledge of using LLMs to accelerate model development, for example through synthesizing training data or automating evaluation.

- Proven ability to own a problem space from 0 to 1, translating vague business problems into production models.

- Comfortable navigating ambiguity and working with competing priorities.

- Strong communication skills to present models and actionable insights to stakeholders with varying levels of technical expertise.

Bonus Points

- Specific examples of recommendation systems, taxonomies, or AI agents that you have built.

- Experience with data engineering, analytics, dashboards, or BI tools.

- Experience with A/B testing or causal analysis.

- An economics or social sciences background, especially any experience analyzing or modeling labor market data.

- Recognized expertise through publications, conference talks, open-source software releases, or other public artifacts related to state-of-the-art tools, models, and techniques.

Our Tech Stack

- Languages: SQL, Python

- Data orchestration: Airflow

- Data storage and warehousing: S3, Glue, Redshift, PostgreSQL, MongoDB

- Machine learning and experimentation: AWS SageMaker

- Visualization and reporting: Looker, QuickSight

- Infrastructure: AWS ecosystem

Your Education

Your alma mater isn’t their focus. Your grit, hunger, and drive are. If you learn continuously, tackle challenges head-on, and know your strengths and gaps intimately—you’re their person.

Location: United States or Canada (Remote, ET Preferred)

Travel Expectations

You may be expected to travel up to once per quarter.

Compensation

The base salary range for this role is $115,000-$140,000. This range reflects the varying levels of expertise and responsibilities that will be determined through the interview process, based on applied experience and other criteria established by the hiring committee.

Hiring Journey

The hiring process is designed to help you assess whether this role and the culture are the right fit based on your unique skills, mindset, and experiences. They move fast and work with intensity, so they want you to get a real sense of that from the start.

Each journey includes a mix of interviews and a performance challenge. For this role, that might look like:

1. Online Application

2. Initial Screen with Director of People & Culture

3. Interview with Hiring Manager

4. Performance Challenge

5. Panel Interview

6. Final Decision

Generally, this entire process takes around 4 weeks, although the timing can vary due to specific candidate circumstances.

Ready to shape the future of work?

They are not just building a company—they are transforming how talent and opportunity connect. Join the driven team united by a commitment to job seekers and the workforce ecosystems they serve.

Company Snapshot:

- Team: 30-50 across US and Canada (hubs in NYC and Toronto)

- Customers: Workforce development agencies and intermediaries, government agencies, employers

- Industry: SaaS/AI technology

- Funding: Bootstrapped 0-1, then raised funding led by JP Morgan

- Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations

Our Core Principles

- Be Curious

- Drive to Outcomes

- Raise the Bar

- Speed Matters

- Own It

- We Over Me

Use of AI in Hiring

They use artificial intelligence (AI) tools to make the hiring process more efficient, consistent, and equitable—never to replace human judgment. AI is used in the following ways:

- Screening support: AI may help compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input.

- Interview support: In some interviews, they may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation.

- Insights, not decisions: AI provides data points to support the team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.

They will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact them to request an accommodation.

They are proud to be an equal opportunity workplace. They celebrate diversity and are committed to creating an inclusive environment for all employees. They do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. They encourage people of different backgrounds, experiences, abilities, and perspectives to apply.

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