Full-Time
DataCamp
1,001-5,000 employees
Online platform for data science education
No salary listed
Senior, Expert
London, UK
Flexible working hours are available.
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- Proven experience in mobile growth (+5 years), with a strong understanding of paid channels, ASO, push notifications, and attribution.
- Strong data analysis skills and the ability to translate insights into actionable strategies.
- Excellent communication and collaboration skills to work effectively with cross-functional teams.
- Innovative mindset with a passion for testing new ideas and driving continuous improvement.
- Focused on achieving measurable results and driving growth for the mobile app.
- Experience with Appsflyer or similar attribution tools is highly desirable.
- Manage and optimize all paid acquisition channels to drive app installs and user engagement.
- Develop and implement ASO strategies to improve our app’s visibility and conversion rates in app stores.
- Set up and maintain accurate attribution models to measure the effectiveness of our marketing efforts.
- Own the Mobile App commercial results. You are the go-to person for everything related to the app.
- Work closely with product, analytics, and growth engineering teams to align on goals and execute growth initiatives.
- Analyze performance data to identify trends, insights, and opportunities for growth.
- Stay up-to-date with industry trends and best practices to continuously improve our mobile growth strategies.
DataCamp is an online learning platform focused on teaching data science skills to individuals and businesses. It offers a variety of courses and learning paths that cover topics such as data analysis, machine learning, and statistics, using popular tools like R, Python, and SQL. Users can learn at their own pace through video tutorials and coding challenges, which are accessible from any web browser. For businesses, DataCamp provides customized plans to help employees improve their data skills, addressing the increasing need for data literacy in the workforce. The platform operates on a subscription model, allowing users to start learning for free but requiring a paid subscription for full access to all courses and features. DataCamp stands out from competitors by specifically targeting the data science niche and offering a comprehensive suite of resources tailored to both individual learners and organizations.
Company Size
1,001-5,000
Company Stage
Early VC
Total Funding
$31.2M
Headquarters
New York City, New York
Founded
2013
Simplify's Take
What believers are saying
- Growing demand for data literacy boosts DataCamp's market potential.
- Partnerships with Alteryx and KNIME expand DataCamp's educational offerings.
- EvolveMe platform partnership enhances DataCamp's reach to younger audiences.
What critics are saying
- Emerging AI models may overshadow DataCamp's educational features.
- Resource strain from high demand for diverse analytics talent.
- Competition from new educational tools like SWiRL.
What makes DataCamp unique
- DataCamp offers interactive, in-browser coding for data science education.
- Courses are taught by experts, covering R, Python, SQL, and more.
- DataCamp for Business provides scalable training for corporate data science teams.
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Benefits
Competitive salary
Stock options
Generous healthcare benefits
Fully paid parental leave
Personal development budget
Personal office equipment budget
International company trips and trainings
Free lunch and healthy snacks
Company News
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Researchers from Stanford University and Google DeepMind have unveiled Step-Wise Reinforcement Learning (SWiRL), a technique designed to enhance the ability of large language models (LLMs) to tackle complex tasks requiring multi-step reasoning and tool use. As the interest in AI agents and LLM tool use continues to increase, this technique could offer substantial benefits for enterprises looking to integrate reasoning models into their applications and workflows.The challenge of multi-step problemsReal-world enterprise applications often involve multi-step processes. For example, planning a complex marketing campaign may involve market research, internal data analysis, budget calculation and reviewing customer support tickets. This requires online searches, access to internal databases and running code.Traditional reinforcement learning (RL) methods used to fine-tune LLMs, such as Reinforcement Learning from Human Feedback (RLHF) or RL from AI Feedback (RLAIF), typically focus on optimizing models for single-step reasoning tasks. The lead authors of the SWiRL paper, Anna Goldie, research scientist at Google DeepMind, and Azalia Mirhosseini, assistant professor of computer science at Stanford University, believe that current LLM training methods are not suited for the multi-step reasoning tasks that real-world applications require.“LLMs trained via traditional methods typically struggle with multi-step planning and tool integration, meaning that they have difficulty performing tasks that require retrieving and synthesizing documents from multiple sources (e.g., writing a business report) or multiple steps of reasoning and arithmetic calculation (e.g., preparing a financial summary),” they told VentureBeat.Step-Wise Reinforcement Learning (SWiRL)SWiRL tackles this multi-step challenge through a combination of synthetic data generation and a specialized RL approach that trains models on entire sequences of actions. As the researchers state in their paper, “Our goal is to teach the model how to decompose complex problems into a sequence of more manageable subtasks, when to call the tool, how to formulate a call to the tool, when to use the results of these queries to answer the question, and how to effectively synthesize its findings.”SWiRL employs a two-stage methodology. First, it generates and filters large amounts of multi-step reasoning and tool-use data
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Unfortunately for Google, the release of its latest flagship language model, Gemini 2.5 Pro, got buried under the Studio Ghibli AI image storm that sucked the air out of the AI space. And perhaps fearful of its previous failed launches, Google cautiously presented it as “Our most intelligent AI model” instead of the approach of other AI labs, which introduce their new models as the best in the world.However, practical experiments with real-world examples show that Gemini 2.5 Pro is really impressive and might currently be the best reasoning model. This opens the way for many new applications and possibly puts Google at the forefront of the generative AI race. Source: Polymarket. Long context with good coding capabilitiesThe outstanding feature of Gemini 2.5 Pro is its very long context window and output length
It’s amazing how, no matter how far technology moves forward, people will still want a taste of the old-school offerings that came before. The roulette market is a prime example, one that’s rich with innovation but that stays true to its roots. Among the many advanced options that push the boundaries of roulette, there are [] The post 20p Roulette Highlights Continued Popularity of Retro Games appeared first on TechMoran.
BOSTON, Jan. 28, 2025 /PRNewswire/ -- American Student Assistance® (ASA), a national nonprofit changing the way kids learn about careers and prepare for their futures, today announced the expansion of its EvolveMe partner network, including CodingNomads, ESAI, Vero Learning, Wicked Saints Studios, DataCamp, Milestone C, and SkillUp Coalition. Launched in 2023, EvolveMe® is an award-winning, skill-building and career experimentation platform that incentivizes young people to take actions that advance their career interests. Through the platform, teens have access to more than 180 diverse career experimentation tasks – powered by innovative partner organizations – with an 81 percent completion rate.Part of ASA's digital ecosystem of free career readiness experiences, EvolveMe enables teens to discover and engage in high-quality, credible career experimentation activities—called Tasks—including virtual internships, AI-powered career coaching, mock job interviews, coding courses, and virtual career mentorships; and develop transferable skills they can apply to any job. These tasks involve many different engaging formats, such as watching videos and taking quizzes, playing games, and completing mini-lessons or quests. For tasks completed, teens earn points they can redeem for gift cards to their favorite retail, restaurant, and entertainment brands
"Through this collaboration, we're integrating KNIME's powerful visual workflows with DataCamp's unique learning experience, enabling users to gain insights faster and more effectively.