Peyman MohCEO

London, UK

Tel: +44 20 3807 1662 [Ext. 12]

A self made entrepreneur with over 18 years of experience in new business development, management, business planning, software development,  and system analytics, within Oil & Gas, Commodities Trading and IT industry.  He has the breadth and depth of experience needed to quickly understand businesses needs and craft the most suitable and sustainable solutions.

Areas of expertise
  • Business transformation
  • Strategic Planning
  • Technology Integration
  • Growth strategy
  • Master of Engineering (M.Eng.), Energy,Environmental Technology and Economics, London City University, UK ; Engineering and Mathematical Sciences School
  • MBA, Hull Business School, University of Hull, UK

Peyman is an Iranian born entrepreneur and founder of Harvey Milton. After 28 years living and working in Tehran, he decided to study MBA (2005) in the UK. Furthermore he choose to focus his knowledge in wider aspects of economy and energy by completing the MSc in Environmental Technology, Energy and Economics, from the school of Maths and Engineering City University London shared joint modules with Cass Business School.

Through his extensive network, and passion for the general energy and industrial commodity issues; he has been employed by others to develop several businesses from scratch both in the UK and Iran.

In 2008 he ventured out on a consultancy which seeks to share his extensive experience and connections. Later on, group of experienced consultants join the leading team to enhance the quality of services and and extend to the new areas.

2008 – Present: CEO, Harvey Milton, London, UK
2007 – 2008: Commercial Manager, Smart Petroleum, London, UK
2004 – 2007: Commercial Manager, NTI, Tehran, Iran
2003 – 2004: Sales Executive, DAEWOO INTERNATIONAL CORPORATION, Tehran, Iran


City, University of London


Contact us at the Harvey Milton office nearest to you or submit a business inquiry online.

  • Machine Learning for the Web

    What is machine learning? In the past year, whether it was during a conference, a seminar or an interview, a lot of people have asked me to define machine learning. There is a lot of curiosity around what it is, as human nature requires us to define something before we begin to understand what its potential impact on our lives may be, what this new thing may mean for us in the future.

    Similar to other disciplines that become suddenly popular, machine learning is not new. A lot of people in the scientific community have been working with algorithms to automate repetitive activities over time for several years now. An algorithm where the parameters are fixed is called static algorithm and its output is predictable and function only of the input variables. On the other hand, when the parameters of the algorithm are dynamic and function of external factors (most frequently, the previous outputs of the same algorithm), then it is called dynamic. Its output is no longer a function only of the input variables and that is the founding pillar of machine learning: a set of instructions that can learn from the data generated during the previous iterations to make a better output the following time.

    30th August 2017
  • BIG DATA in the Upstream Oil & Gas industry

    The Big Data terminology, as well as the term “Digital”, covers a lot of different situations of various natures. This short paper aims at clarifying the existing processes and making some proposals for applying a Big Data approach to the Oil & Gas upstream industry.

    16th February 2017