This website uses cookies. By continuing to use this site, you are giving your consent to cookies being used. See our Privacy policy for more info.

Jobs

Specialism
About
Advice
Join Us
Contact

Login / Register

Login

Login using your social profile

Email

Password

Remember Me

Register a new account with Harnham

Forgot your password?

Email Please supply a valid email Please supply a valid email

Please check your email inbox. If we were able to find an account using the email address you provided, we will have sent instructions to you on how to reset your password. If you have not received anything after an hour or so, it may mean you entered your email address incorrectly or do not have an account with us.

Daniel Lewis

Senior Manager - UK

Send me a message

Name

Company

Local File Dropbox Google Drive

Email address

Your message

Send me a message Send me your CV Send me your job vacancies

Send me a message

Name

Company

Local File Dropbox Google Drive

Email address

Your message

Send me your CV

First name

Last name

Email

Local File Dropbox Google Drive

Specialisms

Clear

Marketing & Insight

Marketing Analyst
Campaign Analyst
Customer Insight
Data Planning
Statistical Analyst
Pricing Analyst

Data & Technology

Big Data
Data Architecture
Business Intelligence
Data Visualisation
Data Management
Data Governance
Software Engineer

Digital Analytics

Web Analyst
Digital Marketing Analyst
Conversion Rate Optimiser
Digital Implementation
Media Analyst & Adtech

Risk Analytics

Decision Science
Portfolio Analyst
AIRB Modelling
Fraud Analyst
Financial Crime Analyst

Computer Vision

Robotics & Autonomy
Medical Imaging
Facial Recognition
Virtual & Augmented Reality
Verification & Security

Data Science

Quantitative Analyst
Data science
Deep Learning and AI
Natural Language Processing

Internal

Locations

Clear

UK

East Anglia
Scotland
South West
Wales
East Midlands
London
North East
North West
West Midlands
South East
Yorkshire

USA

Northeast
Southeast
Midwest
Southwest
West
Northwest

Germany

Bayern
Hessen
Nordrhein Westphalen
Berlin
Hamburg
Stuttgart

Benelux

Netherlands

North
South
East
West
Amsterdam

Belgium
Luxembourg

Nordics

Denmark
Norway
Sweden
Finland

France
Southern Europe

Spain
Gibralter
Malta

OTHER

Send me your job vacancies

Name

Company

Telephone

Email

Enquiry

Local File Dropbox Google Drive

Bio

Dan started his career in recruitment as part of Harnham’s 2013 graduate scheme as a member of the recently formed Digital team. He has helped grow the team, and progressed through to Manager level, where he is now looking to continue Harnham expansion in the Digital Analytics and Optimisation space.

My jobs

CAUSAL INFERENCE SPECIALIST - DATA SCIENTIST

Salary

£11000 - £100000 per annum + Bonus + Benefits

Location

London

Description

This company is a world renowned multi-billion pound social media company are looking for a Data Scientist specializing in causal inference to join their ranks

Reference:

54042/AMH

Expires on

Read more

ADD TO SHORTLIST

Robotics Software Engineer

Salary

£65000 - £75000 per annum + Equity + Benefits

Location

London

Description

This disruptive unicorn start-up are looking for Robotics experts to join them in their drive to revolutionise ecommerce.

Reference:

55964/AMH

Expires on

Read more

ADD TO SHORTLIST

BioTech Data Scientist

Salary

£110000 - £120000 per annum + Bonus + Benefits

Location

London

Description

This European BioTech company are looking for Data Science experts to join them in their drive to revolutionise their manufacturing process.

Reference:

57921/AMH

Expires on

Read more

ADD TO SHORTLIST

Computer Vision Scientist

Salary

£55000 - £65000 per annum + Bonus + Benefits

Location

London

Description

This world leading company are looking for Computer Vision experts to join them in their mission to expand into the UK!

Reference:

50623/ALMH

Expires on

Read more

ADD TO SHORTLIST

Show more

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Opportunity Knocks: Media Trading Desks Move In-House

It’s anticipated that by 2022, 80% of the advertising process will be automated. With the remainder of the process made up of elements that rely on human drivers, such as brand value and storytelling, we will have reached peak automation. Programmatic is playing a huge role in this transition, dominating the majority of mobile display and TV advertising. With the promise of more targeted ads, more and more marketers are pointing their budgets in this direction. The consequences of this, however, could have a lasting impact. Larger agencies are already introducing their own Programmatic teams, whilst Adobe believe that 62% brands will bring their media buying in-house by 2022, opening the door for an array of new opportunities. Moving Home There are several reasons that brands are choosing to bring their media buying in-house. First and foremost, with more and more budget directed towards Programmatic, the ability to automate their buying has a significant appeal. With the technology now available to do so, keeping this in-house has a number of benefits: Control: Brands can have greater control over how they spend their budget, giving them more autonomy over every stage of the process. Transparency: By owning their media buying, brands can gauge a better understanding of their ROI. Engagement: Customers continuously move from channel to channel. Keeping buying in-house helps brands keep up. Leverage: Brands can leverage their first-party data to create and execute in-house strategies. The last of these is particularly important. Following the introduction of GDPR, brands are under a significant amount of scrutiny regarding how they use customer data. By keeping this in-house, brands can have more control over how their data is both stored and used, without sharing it with third parties. Making the Investment Naturally, this change to the advertising landscape is already having implications across the wider industry. Sir Martin Sorrell, formerly of WPP, believes that brands moving in-house will be a “short lived trend” brought on by a reaction to “serious economic conditions”. However, this may not necessarily be the case. In addition to the benefits listed above, the significant investment required to move Programmatic in-house means that brands are likely to look to this as a longer-term solution.This not only involves investment in a DMP and the right technology but, more crucially, in building the right team. Without this team, any in-house venture is unlikely to succeed, regardless of technological investment. On Your Doorstep The good news is that this provides several new opportunities for Digital Analytics professionals. With 39% of Marketing Executives believing that a skills shortage is responsible for holding back Programmatic growth, there is a huge demand for the right talent, both permanent and contract. And, with this skills shortage, there is opportunity for Web and Marketing Analysts to expand their skillsets and move into the position of Media or Audience Analyst. By upskilling in media trading platforms such as AppNexus and DoubleClick, digital analysts can further enhance their expertise. When combined with the ability to visualise using Python or R they find themselves well positioned for some of the most in-demand roles around. If you’re looking for the opportunity to play an instrumental role in growing an in-house team, we may have a role for you. Take a look at our latest jobs, or get in touch by calling us on +44 20 8408 6070 or emailing info@harnham.com. This article was originally written for London MeasureCamp in September 2018.

by Daniel Lewis

05. December 2018

Web analytics recruitment in 2015

The UK analytics market is an ever-shifting landscape, with technical skills that flit in and out of favour more frequently than primary school playground friendships. Recruiting into this market, we at Harnham find the demand for analysts with up-to-date skill sets is a constant. The subtle variants required within these skill-sets coupled with the proficiencies we need to find, seem to also evolve on almost a monthly basis. This means that Harnham need to be as agile in our practices as the candidates we source. This is nevermore clearly illustrated by the fact that one month we can be scouring the country for highly technical Tag Management specialists, and the next, our focus shifts to sourcing 8 new Conversion Rate Optimisation specialists. Moving on to next month, pinning down the elusive and much sought-after Web Analytics / BI / Computer Science / Statistical modelling expert (aka. The mythical “Analytics Unicorn”). The Benefit of Forward Thinking Skillsets The diversity of technical requirements should give tremendous encouragement to any analyst looking to find work – regardless of background and skill-set you possess; there will definitely be no shortage of suitors clamouring for the right expertise. However, it is prudent to be ever mindful, that with this exciting and evolving landscape, there are also risks attached. How often have you heard stories of promised roles not being fulfilled by companies? Or about analysts who join a company to do a specific job, and then have their career development curtailed by lack of long-term strategy, or a lack of knowledge of what to do next for the team? This kind of thing is and does happen regularly. Yet, hope is at hand. If you were to cast your gaze across the Atlantic Ocean to our American cousins, you would find that Analytics is a settled and well established practice, where Chief Data Officers regularly sit on the board and the Analysts control business strategy. Becoming a Unicorn Harnham’s team in New York City have found the lines between offline and online blur when stateside – Web Analysts do advanced statistical analysis and modelling, Stats Analysts measure conversion rates and so on and so on. The US is trying to breed their own “Unicorns”, rather than chase them. As the dust starts to settle in the UK, and the market definition solidifies to become as robust as it is in the States; teams will grow and budgets will increase as the market develops. The senior analysts of today will become the thought leaders and managers of tomorrow.

by Daniel Lewis

01. October 2015

A data janitor, the sexiest job of the 21st century

A job invented in Silicon Valley is going mainstream as more industries try to gain an edge from big data.The job description “data scientist” didn’t exist five years ago. No one advertised for an expert in data science, and you couldn’t go to school to specialize in the field. Today, companies are fighting to recruit these specialists, courses on how to become one are popping up at many universities, and the Harvard Business Review even proclaimed that data scientist is the “sexiest” job of the 21st century.Data scientists take huge amounts of data and attempt to pull useful information out. The job combines statistics and programming to identify sometimes subtle factors that can have a big impact on a company’s bottom line, from whether a person will click on a certain type of ad to whether a new chemical will be toxic in the human body.While Wall Street, Madison Avenue, and Detroit have always employed data jockeys to make sense of business statistics, the rise of this specialty reflects the massive expansion in the scope and variety of data now available in some industries, like those that collect data about customers on the Web. There’s more data than individual managers can wrap their minds around—too much of it, changing too fast, to be analyzed with traditional approaches.As smartphones promise to become a new source of valuable data to retailers, for example, Walmart is competing to bring more data scientists on board and now advertises for dozens of open positions, including “Big Fast Data Engineer.” Sensors in factories and on industrial equipment are also delivering mountains of new data, leading General Electric to hire data scientists to analyze these feeds.The term “data science” was coined in Silicon Valley in 2008 by two data analysts then working at LinkedIn and Facebook (see “What Facebook Knows”). Now many startups are basing their businesses on their ability to analyze large quantities of data—often from disparate sources. ZestFinance, for example, has a predictive model that uses hundreds of variables to determine whether a lender should offer high-risk credit. The underwriting risk it achieves is 40 percent lower than that borne by traditional lenders, says ZestFinance data scientist John Candido. “All data is credit data to us,” he says.Data scientist has become a popular job title partly because it has helped pull together a growing number of haphazardly defined and overlapping job roles, says Jake Klamka, who runs a six-week fellowship to place PhDs from fields like math, astrophysics, and even neuroscience in such jobs. “We have anyone who works with a lot of data in their research,” Klamka says. “They need to know how to program, but they also have to have strong communications skills and curiosity.”The best data scientists are defined as much by their creativity as by their code-writing prowess. The company Kaggle organizes contests where data scientists compete to find the best way to make sense of massive data sets (see “Startup Turns Data Crunching into a High-Stakes Sport”). Many of the top Kagglers (there are 88,000 registered on the site) come from fields like astrophysics or electrical engineering, says CEO Anthony Goldbloom. The top-ranked participant is an actuary in Singapore.Universities are starting to respond to the job market’s needs. Stanford University plans to launch a data science master’s track in its statistics department, says department chair Guenther Walther. A dozen or so other programs have already been started at schools including Columbia University and the University of California, San Francisco. Cloudera, a company that sells software to process and organize large volumes of data, announced in April that it would work with seven universities to offer undergraduates professional training on how to work with “big data” technologies.Cloudera’s education program director, Mark Morissey, says a skills shortage is looming and that “the market is not going to grow at the rate it currently wants to.” That has driven salaries up. In Silicon Valley, salaries for entry-level data scientists are around $110,000 to $120,000.Others think the trend could create a new area of outsourcing. Shashi Godbole, a data scientist in Mumbai, India, who is ranked 20th on Kaggle’s scoreboard, recently completed a Kaggle-arranged hourly consulting gig, a new business the platform is getting into. He did work for a tiny health advocacy nonprofit located in Chicago and is now bidding on more jobs (he earns $200 per hour, and Kaggle collects $300 an hour). His Kaggle work is part time for now, but he says it’s possible that it could be his major source of income one day.To the data scientists themselves, the job is certainly less sexy than it’s being made out to be. Josh Wills, a senior director of data science at Cloudera, says most of the time it involves cleaning up messy data—for example, by putting it in the right columns and sorting it.“I’m a data janitor. That’s the sexiest job of the 21st century,” he says. “It’s very flattering, but it’s also a little baffling.” Click here for the article on the web.

by Daniel Lewis

17. July 2013

View all blogs

recently viewed jobs

Giving Back

Read about Harnham's corporate social responsibility initiatives

Find our more about the causes we support.

READ MORE

RECRUITMENT
ABOUT US
CONTACT
OTHER

© 2018 Harnham Search and Selection Ltd. All rights reserved

Registered office: 3rd Floor, Melbury House, 51 Wimbledon Hill Road, Wimbledon, SW19 7QW.
Harnham Search and Selection is a registered company in England and Wales. Company registration number: 05723485

Website by 4MAT / Designed by Brand Nu

Keyword: No Keyword

Options: 262, 1035

Location:

User Profile Page