Unlearn AI

Director of Product Marketing

San Francisco, California, United States

$180,000 – $240,000Compensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Consumer SoftwareIndustries

Requirements

Candidates should possess a Bachelor’s degree in Marketing, Business Administration, or a related field, with a Master’s degree or MBA preferred. They must have over 10 years of marketing experience, showcasing a strong balance of strategic leadership and hands-on execution. A proven track record in leading teams and driving key initiatives is essential, along with deep expertise in product marketing, including customer and market insights. Experience in the pharmaceutical, life sciences, or healthcare technology sectors is strongly preferred. Excellent written and verbal communication skills are required, along with the ability to use data and statistical analyses for marketing decisions. Candidates should be nimble and adaptable, thriving in fast-paced environments, and have experience marketing Generative AI-powered products or AI solutions. Relevant marketing certifications are a plus.

Responsibilities

The Director of Product Marketing will lead the marketing efforts aligned with the product roadmap, driving the company’s product marketing strategy and execution. This role includes defining the vision and executing campaigns, analyzing performance metrics, and contributing to marketing initiatives. The individual will collaborate with product development teams to create marketing strategies for products, translating complex concepts into accessible content. They will analyze market trends and customer insights to inform decisions, design and implement multi-channel marketing campaigns, and support sales teams with compelling marketing collateral. Budget management and team leadership are also key responsibilities, along with establishing KPIs to measure effectiveness and collaborating cross-functionally with various teams.

Skills

Product Marketing
Strategic Thinking
Marketing Initiatives
Performance Metrics
Brand Positioning
Market Share

Unlearn AI

Creates AI-driven digital twins for healthcare

About Unlearn AI

Unlearn.AI creates digital twins of patients using artificial intelligence, which are virtual replicas that simulate potential health outcomes. This technology allows healthcare providers to predict how a patient's health may change over time, leading to more informed treatment decisions. The primary clients include healthcare providers and pharmaceutical companies, who can use these digital twins in clinical trials to simulate control groups, potentially speeding up drug development and approval processes. Unlearn.AI differentiates itself by offering a unique simulation technology that reduces the need for actual human control groups, which can save time and resources. The company's goal is to enhance decision-making in patient care and drug development through precise health outcome predictions.

Key Metrics

San Francisco, CaliforniaHeadquarters
2017Year Founded
$127.1MTotal Funding
SERIES_CCompany Stage
AI & Machine Learning, HealthcareIndustries
51-200Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
401(k) Company Match
Unlimited Paid Time Off
Paid Holidays
Commuter Benefits
Paid Parental Leave
Company Equity

Risks

Over-reliance on AI data may lead to inaccuracies in trial outcomes.
Increased competition from companies like Consilx and Aicure could impact market share.
High clinical trial failure rates could affect perception of Unlearn AI's effectiveness.

Differentiation

Unlearn AI's TwinRCT uses digital twins to enhance clinical trial precision.
The company offers TrialPioneer, a free tool for innovative trial design exploration.
Unlearn AI's digital twin technology reduces the need for human control groups.

Upsides

AI in clinical trials market expected to reach $2.74 billion by 2030.
Partnership with ProJenX highlights AI's potential in specific therapeutic areas.
TwinRCT 3.0 enhances decision-making in Phase II trials for better outcomes.

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