Job Description

OpusClip

is the world's No.1 AI video agent, built for authenticity on social media.

We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used OpusClip to enhance their social presence.


We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including SoftBank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (SaaStr), Samsung Next, GTMfund, Alumni Ventures, and many more.


Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024.


Headquartered in Palo Alto, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values:


Be a Champion Team Prioritize Ruthlessly Ship fast, Quality Follows Obsess over customers
Be a part of this exciting journey with us!

About the Role

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We're looking for a Data Science Lead to build and scale Opus's data capabilities. This role sits at the crossroads of data engineering, applied data science, and product strategy. You'll lead high-impact projects across growth, CRM, customer experience, payments, web tracking, experimentation, and LLM-driven analytics--working closely with cross-functional partners to drive measurable business outcomes.


This is a hands-on role: you'll define data vision, architectural systems, and roll up your sleeves to build pipelines, models, and advanced analyses that power Opus's growth.

Responsibilities

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Data Engineering & Infrastructure

Design, implement, and maintain robust pipelines across multiple sources, including GCS, MongoDB, and third-party SaaS platforms. Ensure scalable ingestion, transformation, and governance of structured and unstructured data.

Applied Data Science & Analytics

Lead advanced analyses across growth, CRM/CX, payment flows, and web tracking. Build marketing attribution models to measure ROI and optimize spend. Analyze user lifecycle and retention patterns, including churn risk, reactivation triggers, and CLV. Develop predictive models on user behavior to power personalization and recommendations. Create user segmentation and tagging frameworks to enable targeted engagement strategies. Evaluate CX metrics (NPS, CSAT, support efficiency) to inform product and ops improvements. Establish best practices in A/B testing and post-experiment evaluation. Prior experience in these areas is highly valued.

Experimentation & Insights

Partner with product and business teams to design experiments and interpret results. Drive rigor in experiment design, metric selection, and causal inference.

Leadership & Strategy

Define the data science roadmap / priority and align it with company goal. Mentor and grow a scrappy, high-performing team of data engineers and analysts. Act as a thought partner across GTM and BD initiatives, enabling data-driven decisions.

Requirements

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Experience

8 years of experience in data-related roles, with a mix of individual contributor (IC) and manager/lead responsibilities. Proven track record of leading teams and projects end-to-end, while still being hands-on when needed. Strong ability to mentor and grow talent in a fast-paced, high-ownership environment.

Education

Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, or related). Master's degree preferred, though not strictly required, if compensated by strong industry experience.

Technical Expertise

Strong proficiency in Python and SQL, with hands-on experience across the data lifecycle. Experience with the modern data stack (BigQuery, dbt, Superset, Statsig). Solid data engineering skills with cloud storage (e.g., GCS), NoSQL databases (e.g., MongoDB), and SaaS integrations. Familiarity with workflow orchestration (e.g., Airflow) to automate and manage pipelines. Mastery of working in notebooks (e.g., Jupyter, Databricks), comfortable digging into raw data repositories and producing reproducible analyses. Familiar with LLM and agent workflows, curious and eager to push the frontier. Strong end-to-end development skills: from data ingestion and cleaning through modeling, analysis, deployment, and monitoring.

Analytical Excellence

Deep experience in A/B testing, experimentation platforms, and post-experiment analysis. Strong statistical intuition with the ability to translate results into actionable insights.

Domain Experience

Exposure to CRM/CX, payments, web tracking, and user data. Experience building data products that support BD and customer-facing use cases.

Leadership & Collaboration

Ability to balance hands-on execution with strategic leadership. Experience in fast-paced startup environments, collaborating with product, engineering, and GTM teams.

Nice to Have

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Experience with ML in production, including deployment and monitoring. Interest in building and experimenting with data-driven agents, including prototyping agentic workflows. Familiarity with reinforcement learning and experimentation frameworks, ideally with human-in-the-loop (HITL) evaluation. Working knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS) and RAG pipelines for LLM-powered applications.

EEO

OpusClip is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. OpusClip considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Opus Clip is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.


Compensation Range: CA$160K - CA$200K