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Dan Mano
Smilebox GM - Perion Network (NASDAQ: PERI) ELT (Perion’s Management)
Professional Background
Dan Mano is a highly skilled and detail-oriented process data analyst, bringing over two years of specialized experience in process data analysis, equipped with proficiency in OSIsoft, Python, and SQL. His deep understanding of data optimization practices has been instrumental in enhancing production processes and delivering critical computational research support for various case studies. Dan is adept at converting complex data into insightful dashboards and reports that provide a clear overview of key performance indicators (KPIs). These reports play a crucial role in facilitating data-driven decision-making for primary stakeholders in organizations.
His comprehensive professional journey includes an impressive array of management roles and entrepreneurial ventures. Notably, Dan has served as a General Manager at Smilebox, a renowned platform that allows users to create personalized greeting cards. In addition to his role at Smilebox, he was a co-founder at REACH, where he contributed to establishing a vibrant community and service model. Furthermore, he has played pivotal roles in different capacities, such as an Advisory Board Member at Nanobébé, providing strategic insights to help navigate the business landscape. Dan's consultancy proficiency spans notable firms, including his role as a consultant at NordSec, where he provided expert advisory in cybersecurity, and as an interim Chief Marketing Officer at SWIFT SHIFT, where he demonstrated his strategic marketing capabilities.
His expertise doesn't stop at consultancy, as he also has extensive leadership experience in business development at MyHeritage. Dan has excelled in several positions, including Chief Risk Officer (CRO) and Senior Vice President of Business Development, driving key strategies that accelerated organizational growth. His tenure at MyHeritage marked a significant phase where he leveraged his extensive marketing background to enhance brand visibility and market outreach in the competitive genealogy sector.
Venturing further into his entrepreneurial spirits, Dan was the co-founder and Chief Executive Officer of Glossybox at Rocket Internet SE. His leadership in this global beauty subscription service showcased his ability to innovate and adapt in fast-paced markets. Furthermore, his earlier experiences as a Product Marketing Team Leader at 888holdings and Junior Associate at Naschitz, Brandes, Amir & Co. have cultivated a rich and diverse background that contributes to his current analytical capabilities. Dan has also been at the forefront of innovative startup ventures like tVoutcome and Dasur Ltd., exemplifying his expertise in recognizing market gaps and developing effective business models.
Education and Achievements
Dan's academic credentials are as impressive as his professional achievements. He earned his Master of Business Administration (MBA) in Entertainment and Media Management from the prestigious UCLA Anderson School of Management, where he honed his skills in analyzing media market trends and business strategies. Additionally, he pursued another MBA in Finance at the esteemed London Business School, gaining vital financial acumen that informs his analytical approach.
Before his graduate studies, Dan completed his Bachelor of Laws (LLB) with cum laude honors at IDC Herzliya, excelling in legal studies with a focus on entrepreneurship through the Zell Entrepreneurship Program. This robust educational foundation allows him to intersect legal, financial, and analytical perspectives effectively in his work, particularly in business negotiations and strategic planning. Dan's earlier educational experience at The Hebrew Reali School nurtured his scientific aptitude through a strong physics program, further sharpening his analytical skills.
Notable Achievements
Throughout his career, Dan has achieved significant milestones that highlight his dedication and expertise. As part of Perion Network’s Management Team (ELT), he has actively contributed to strategic initiatives that have elevated company performance. His entrepreneurial ventures, such as launching Glossybox and founding several startups, underscore his innovative spirit and commitment to delivering value through technology and marketing. As a leader in the business development arena, Dan has not only driven growth in established companies like MyHeritage but has also fostered new opportunities in startups, exhibiting versatility across various market sectors.
Dan’s ability to synergize insights from data analysis with his extensive business knowledge sets him apart in his field. His forward-thinking approach and collaborative nature ensure that he builds constructive relationships with stakeholders and team members alike, facilitating an environment conducive to innovation and shared success. With an ever-present passion for data, technology, and entrepreneurship, Dan Mano continues to make impactful contributions in the realm of data analysis, business development, and leadership.
tags':['process data analysis','OSI Soft','Python','SQL','data optimization','computational research','dashboards','KPI','business development','entrepreneurship','data-driven decisions','management positions','consultancy','marketing','risk management','legal studies','MBA','finance','media management'],'questions':['How did Dan Mano develop his proficiency in Python and SQL for process data analysis?','What are the key strategies Dan Mano implemented as a General Manager at Smilebox that contributed to its success?','How does Dan Mano integrate his knowledge from his MBA in Entertainment and Media Management into his current role in data analysis?','What innovative approaches has Dan Mano taken in his various startup ventures like tVoutcome and Dasur Ltd.?','In what ways has Dan Mano’s experience at MyHeritage shaped his understanding of business development in tech-driven markets?','What insights does Dan Mano bring to his role as a member of the Advisory Board at Nanobébé, considering his extensive background in entrepreneurship?']},
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
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Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions.
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Questions about this person based on their background, expertise, and career trajectory.
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
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Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions.
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Questions about this person based on their background, expertise, and career trajectory.
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
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Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions.
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Questions about this person based on their background, expertise, and career trajectory.
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
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Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions.
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Questions about this person based on their background, expertise, and career trajectory.
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions.
items
type
string
questions
description
questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
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title
PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements. Output should be formatted in markdown with headings such as 'Professional Background', 'Education and Achievements', 'Achievements'.
items
type
string
tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
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questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
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tags
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Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
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PublicPersonData
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A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
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title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
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title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
string
questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements. Output should be formatted in markdown with headings such as 'Professional Background', 'Education and Achievements', 'Achievements'.
items
type
string
tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
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questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
string
questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements. Output should be formatted in markdown with headings such as 'Professional Background', 'Education and Achievements', 'Achievements'.
items
type
string
tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
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questions
description
Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
string
tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
items
type
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questions
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
object
summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
string
tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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questions
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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type
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questions
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
items
type
string
title
PublicPersonData
type
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summary
description
A few paragraphs about the person's background, including their education, career history, and notable achievements.
items
type
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tags
description
Tags or keywords that explain this person's professional experience, expertise, skills, and interests, including education, schools, work history, and job positions. Each keyword should be 1-4 words long. Do not include the person's name as a tag.
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Questions about this person based on their background, expertise, and career trajectory. These should be thoughtful, open-ended questions that always include the person's name and are fully stated (e.g., 'How did John Smith develop his expertise in artificial intelligence?') rather than conversation starters.
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