Senior Data Scientist (AI)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Location: Hybrid schedule based at the South Charlotte, NC headquarters Tuesday through Thursday, with fully remote work on Fridays; Remote - USA
Total cash compensation: $155,000β$200,000 per year
Company
is a portfolio of high-growth companies delivering digital consumer experiences and large-scale digital growth solutions for major brands across financial services, retail, real estate, entertainment, home services, and telecommunications.
What you will do
- Build and own production ML and AI solutions end to end, from problem framing through deployment, monitoring, and iteration.
- Build LLM agents and agentic workflows, including prompt and tool design, orchestration, deployment, and monitoring.
- Design offline test sets, automated graders, regression suites, and online experiments that connect model quality to business outcomes.
- Apply traditional ML techniques including classification, regression, clustering, optimization, and experimentation where appropriate.
- Develop production-grade code with engineering partners, including testing, CI/CD, and monitoring.
- Work with clients and partner teams to scope problems, present results, recommend next steps, shape roadmaps, and mentor junior and mid-level data scientists.
Requirements
- Bachelorβs degree plus 6 years of experience, or masterβs degree plus 4 years, or PhD plus 2 years.
- Track record of building and owning end-to-end ML solutions in production, including at least one complex solution operating over several months.
- Experience building LLM agents or agentic workflows using frameworks such as LangGraph or the Claude Agent SDK, or model APIs from OpenAI, Anthropic, or similar.
- Experience designing evaluations for ML or LLM systems, including test sets, business-relevant metrics, human validation of automated graders, and regression detection.
- Strong foundation in classification, regression, clustering, and optimization, including limitations and statistically rigorous evaluation.
- Experience presenting technical work to clients or senior stakeholders and explaining the trade-off between model performance and business value.
- Expert-level Python and SQL, plus proficiency in model deployment and ML operations including version control, CI/CD, unit testing, job orchestration, and containers.
- Experience mentoring data scientists through code review, pairing, or project guidance.
- Experience shaping data science or product roadmaps and understanding how AI/ML solutions affect business KPIs.
- Must not require visa sponsorship or transfer of visa sponsorship, including H-1B, F-1, OPT, STEM-OPT, or TN sponsorship; corp-to-corp work is not available.
Nice to have
- Experience with Databricks, MLflow, or AWS.
- Experience with call center, telecommunications, or marketplace data.
Culture & Benefits
- Full-time employment with health, dental, vision, life, disability, flexible spending, and employee assistance benefits.
- 401(k) with company match and paid parental bonding benefits.
- Flexible paid time off, with 20 days accrued annually and 25 days after five years of service.
- Client-facing, technically rigorous environment emphasizing measurable evaluation, practical shipping decisions, automation, and mentoring.
Hiring process
- Expect live conversations with RV teammates before an offer; hiring is not conducted through text, social media, or email only.
- Official recruiting communication uses or portfolio-company email domains; candidates will not be asked to send money, buy equipment, or share financial account information.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ
ΠΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ. ΠΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ Β«ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡΒ» ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β