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Ten Days That Changed Harnham



These are the dates over the past decade that truly made a difference to what started life as an extremely small business with big ambition, all from a normal living room in Wimbledon, London UK in Simon Clarke's (Harnham's founding partner) home with David Farmer. Both former recruiters with a vision, missing a key factor to grow the business - Kat Heague. 

The important dates in a business' history are not always seemingly the biggest or the flashiest to others but are pivotal to how we have become the world's leading data and analytics recruitment company.


09.04.06 The day Harnham was founded, in Simon’s lounge
10.23.06 The date we placed our 1st candidate
10.10.07 We moved into our 1st official office on Graham Road, Wimbledon
07.22.11 This was the date we placed our 1000th candidate in the UK
11.01.11 The team moved to our current office - The Broadway, Wimbledon
10.01.12 Made Our First Non-UK placement
09.01.14 Began working in the USA
03.20.15 Harnham won a Global award for the 'Best Staffing Firm to Work For' award at Staffing Industry Analysts event in San Diego
08.03.15 We opened our first New York office. We have since moved to just off Wall Street
10.01.16 Opened our first office in San Francisco



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Making It As A Woman In Data Science: An Interview with Ashley Holmes

Meet Ashley Holmes. Senior Data Scientist for a firm working to improve healthcare. Or rather, the healthcare system.                   It’s been an unusual year by all accounts. Most jobs have moved online for the foreseeable future, yet jobless rates climb. Everyone is learning to pivot and accelerating their focus and skillsets. It’s also a time to evaluate where you are in your career and where you want to go. So, from time to time, we find it’s best to hear some stories directly from those in the field.  Ashley's story begins with a desire to become a math teacher which in later years included Computer Science classes. A girl with a talent for math taking computer classes? This is her story: What drew you to Data Science from your original education focus? I’d wanted to be a middle or high school math teacher since I was 12 years old. In college, I discovered part of the math major required students to take one computer science course. I took the computer course my first semester of college, and really liked it. Programming was fun! So, to my Math major, I added a Computer Science minor in which I was the only woman. I recall a course in Operations Research in which we’d used mathematics to answer problems in healthcare by using linear algebra to optimize a design for a staffing schedule. This staffing schedule would used by surgeons for operating rooms. Who knew there was a field where you could solve healthcare problems with math and Data? I didn’t, but now that I knew, I dug in. Enter Binghamton University’s Systems Science and Industrial Engineering Department. Though at the time, Master’s Degrees in Data Science didn’t exist yet. But this program at Binghamton had a concentration for healthcare systems. This concentration had it all – courses for Data Science skills like Statistics, Machine Learning, and Artificial Intelligence.  After some of my own horrifying interactions with the healthcare system in the US, and realizing I could use my skills in Math and Computer Science to improve it, then that’s what I wanted to do.  With a graduate research assistantship from The Watson Institute for Systems Excellence (WISE) at Binghamton University, I found myself in the process engineering department at a large care management organization in New York City. It was there I got some real-world experience using clinical Data collected by the hospital to improve processes and solve problems the company had been facing. I was hooked and so my pivot from Math Teacher to Data Scientist.  It's been 10 years since you started on this path, it seems, what changes have you seen in women in the field and/or STEM focus of young women still in school?  While R and Python are taught a lot more in required courses, there was no such thing as a Data Science Masters Degree when I was in school. Most of the Data Scientist’s I know have Mathematics, Computer Science, or Engineering degrees. Though we did some light coding in my grad school courses, most of my real programming skills have come from my graduate research assistantship and various jobs I’ve had. Talk about on the job training! When it comes to women in the field, that has grown significantly thanks to hackathons, events, and groups tailored to encourage women to enter the field.  What Do You Think Now?  In 2018, I heard about a non-profit hackathon in Boston called TechTogether whose mission was to end the gender gap in technology, which I thought was amazing. I’m also now part of a few professional groups for women in STEM that meetup in person and have conferences (pre-COVID) or at least have Slack channels.  These advances for women in technology have been great, but there is still a lot of work to be done. I actually attended a talk yesterday by Melinda Gates (who was herself a computer science major) about how the pandemic is affecting women and girls, who mentioned that in the late 80’s when she was in school, women made up about 35% of computer science majors, whereas now in 2020 it’s down to 20%.  Wait, it's Declined? Why is it Do You Think? I was curious about this too. So, I did some digging to try and find data on this, and came across this NPR article which suggests that the share of women in computer science started falling at roughly the same moment when personal computers started showing up in US homes in significant numbers. It was at this time, computers in homes were mostly for gaming, and "computers are for boys" became a popular narrative. A 1990 study shows that families became more likely to buy computers for boys than for girls, even when their girls were really interested in computers. As those kids got to college, computer science professors were increasingly men, and increasingly assumed that their students had grown up playing with computers at home. Surprisingly, this extended even to the 2010s, because I only had one female professor in my computer science department; the rest were male. Not that they were bad professors by any means, but it seemed to me even then that it was much more difficult for women to break into the profession and actually succeed. Needless to say, I was shocked (and thrilled!) when I first read the book Hidden Figures, and found out about NASA's women computers who were essential to putting human beings on the moon.  I think more stories like this have come out since I was in school...I also remember hearing that Edie Windsor, who was already a hero of mine for her LGBTQ rights activism, was a technology manager at IBM. As these stories have continued to come out, I think more women have been able to see themselves as able to do these kinds of jobs, and that is part of the reason we are on the rebound. Though 2020 has been an unusual year by all accounts, it is also the beginning of a decade. What do you see for the future of women in data science and what has your experience been? With the prominence of social media now, I think it’s becoming much easier to find women in your field to connect with and ask for advice and support, and I think this is true for both young girls potentially interested in data career paths and professionals already in the industry.   What steps would you recommend to young professionals entering the data professional path or those looking to change careers? Any job or networking trade secrets you wish you'd known before finding your current position?  Being part of a community and making connections with other women in the field has been very helpful both personally and professionally. Join a club: Girls Who CodeGirlstartSociety of Women EngineersCheck out conferences like Grace Hopper and Women Impact Tech. Just knowing that there are women out there with jobs that you’ve never heard of can be really beneficial to believing that you can do it yourself. Look at people with the job titles you’re interested in, and see what they’ve done in the past as far as jobs, education, etc. Network and establish relationships with other women in your field. This is a very valuable tool both for getting a job and for general professional support. Take every opportunity to network that you can; I’ve gotten most of my jobs through networking and knowing people.  As a Senior Data Scientist and a woman what challenges do women still face in the industry and what's something surprising you've encountered that helped you grow either personally or professionally? I think women still face a lot of challenges in the industry. Firstly, there are just so few of us. In most of my jobs (except for my current one), Data Science teams are largely made up of men.  Document your accomplishments throughout your job and bring it with you when it’s time to talk promotions and raises. It is absolutely crucial to be able to speak up for yourself and be your own biggest cheerleader. I used to think that the way to advance through a career was just doing excellent work and waiting for someone to notice you and give you a raise or a promotion. I’ve found that isn’t true at all, and if you aren’t talking about your own accomplishments, who else is going to? In that same vein, finding mentors, coaches, and sponsors is critical. Finding someone who has seen your work and can speak about it and you to other people is incredibly important.  Your Best Advice? My best advice is to apply for the job, even if you don’t think you’re 100% qualified. If you’re looking for a role in Data Science, Harnham may have a job for you. Check out our current opportunities or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Alyssa Liew

Alyssa Liew

03. December 2020

The Science Behind the Sales: Statistical Modelling and Consumer Insights

Black Friday, once reserved for the Friday after Thanksgiving, has a new lease on life. It’s not just one day a year. Now, it can be any day of the year. Why? Customers the world over appreciate the deals and discounts as they get ready for the holidays, and the insights gleaned from previous years help businesses determine what will sell best in the current year.  Add in the rise of mobile marketing in which you can buy anything, anywhere, anytime, and more people working from home than ever before, and you have the recipe for Black Friday every day. Especially once the leaves begin to Fall and the holiday season comes knocking at our doors. Behind Advanced Analytics & Insights within the Data profession, there are a host of professions which together help to create the products and launch them. Who could imagine the science behind the sales? Five Important Roles Behind Advanced Analytics & Insights There’s a reason that Data professionals are no longer siloed and must work across and within departments. Data influences every decision within business today. So, having the right people on your team in the right roles can ensure your business thrives. Marketing Analyst Using a spoke-and-wheel analogy, the Marketing Analyst is the spoke. These are the professionals central to taking the information from their Campaign Analysts, Pricing Analysts, and Statistical Modelling experts to determine what will sell best and what price. In essence, their research and Data helps companies figure out ‘what the market will bear.’ Campaign Analyst Focused campaigns to a target market will find a Campaign Analyst understands consumer behaviors. Once the customer is understood – what they buy, when they buy, why and how they buy – can help analysts measure, review, and justify each campaign to justify ROI.Consumer Insights While the Campaign Analyst is focused on targeted campaigns to specific customers, the Consumer Insights Analyst helps businesses tailor their marketing strategies to meet the needs of those customers. All of them. Whether they’re part of a targeted marketing campaign or if they’re prospective clients ‘window shopping’ when they download a ‘free product or click on an email’. Understanding these consumers helps to convert from passing interest to the purchase of a product or service. Statistical Modelling Analyst Do you love puzzles? A jumble of pieces which need to be put together so everyone can see the full picture?  Statistical Modelling are the jigsaw puzzle solvers of the Marketing department. These professionals pull together data from multiple sources and analyze the information to help form a clear picture of their ideal consumer. Toss in a bit of psychology – why customers do what they do and predict what they might do next – and your executives will understand the best way to distribute funds to grow their business. Pricing Analyst It seems simple enough. Determine how much it cost to produce a product or service and mark it up to make a profit, right? Not exactly. These days, calculating not only what it cost to make a product, any overhead to consider, and how much you need to mark it to make a profit is a complex prospect. Factor in what your competition is doing…on a global scale. Consider the fickle buying power of consumers – some days money flows and some days it’s reigned in tight. How do you determine the best price at the right time to ensure maximum profit while keeping pulse on spending patterns? Pricing Analysts take complex data, study customer spending habits, and conduct analyses on what the math says and what the impact might be. So, back to Black Friday sales. Taking what we know of the roles which help businesses set the tone for their marketing strategies, Black Friday every day makes sense. We’re home more. The lines between work and family life are blurred, but computers and phones are at our fingertips, and everyone delivers what we need right to our door. Why not get a jump on your holiday shopping? And once that’s done, you can focus on what your plans are for the future. Are you looking for a career change or just want to see what the market looks like within the Data professionals industry? There is plenty of information to be collected and analyzed. What role might you fill? If you’re looking for a role in Data & Analytics or are interested in Advanced Analytics & Insights, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Hillary Tran

Hillary Tran

12. November 2020

Jumpstart Your Job Search Now and in the Years Ahead

COVID-19 may have rocked the world of employment, but it also created a whole new series of opportunities. If you are looking for work, there are a few updates to the rules of the job search. Not rules, really. More preferred guidelines. A Note on the Guidelines of the Job Search Remember when your work experience was honed to two pieces of paper – your resume and cover letter – and you hoped it made it to the hiring manager? Well, there are a lot more direct ways to get there and plenty of opportunities abound to help you stand out from the crowd. It’s not just your educational experience. In fact, today’s hiring is much more about emotional intelligence, collaboration, and how you use what you’ve learned in previous roles. Among the negative notes, there are a host of positive movements for jobseekers with both established and startup firms. And sometimes, even within a legacy firm which has pivoted with the changes of our new world of work. Thread the Needle of Responsibility Google and IBM may be leading the charge to hire without use of a degree, but most businesses still want that piece of paper. How you present it is another matter. Think video, project portfolios, and online forms via application tracking systems (ATS). That’s just to get you in the door. The more important hurdle is understanding the nuances of your role and responsibilities. The list of qualifications and duties has always been part of the job search. Do you fit all the requirements? Can you handle all the responsibilities? Did you read between the lines to understand what the company hopes will find in their ideal candidate to help them meet their business goals and objectives?  Below are some questions you might ask yourself when reading through job descriptions or considering where you’d like to apply: Are you able to not only craft reports, but also see patterns to help you gain insight into what the reports are telling you?From this, can you not only discuss it with your colleagues and teammates, but also across departments, executives, and stakeholders?Can you not only explain the patterns to both technical and non-technical audiences, but do so across multiple projects?What challenges will you face and how will you solve them?How well do you manage your time? Can you step in to lead a team or do you prefer to work on your own? Could you be flexible between the two?Are you able to build relationships both internally and externally – teammates, vendors, executive leaders, department heads, and the board room.Do you have emotional intelligence? Can you take ownership of a project and hold yourself and others accountable?Do you show initiative? Not just in diving into a project, but asking questions. Can you ask objective questions playing devil’s advocate on one side and seeing the possibilities on the other? These are wide open questions to challenge yourself. Some are leadership-centric. Some are simply ‘can I do the job?’ questions. But, ultimately, it’s these kinds of questions which are asked in interview under the purview of seemingly inane questions. They’re meant to make you think and for the hiring manager to see how you think. 3 Surprising Ways to Stand Out in Your Job Search With the rise of remote working, Zoom, and Slack, the video interview and application process has gained ground. It’s quickly become the virtual way to seek, apply for, meet with, hire, and work with prospective and current team members. But, if you’re in the tech space, you can go even deeper than video and you’ve got more than project portfolios to fall back on. Write about your experiences – what you’ve learned, where, why, and how. Think Medium’s Toward Data Science. Don’t forget to hit publish! Not a writer? Follow the blog and make comments.Network – this seems like a ‘no brainer’, but in our somewhat virtual world it can be even easier for those who already comfortable in this environment. Whether it’s via LinkedIn or Twitch, you are building relationships to help you move forward in your job search.Use your skills to help you run and track your job search more efficiently.  If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

McElla Pappas

McElla Pappas

29. October 2020

The Surprising Collaboration of Ada Lovelace, Charles Babbage, and Alan Turing

What do you get when you combine Amelia Earhart with Ada Lovelace? A Data Visualization Engineer ready to work with an aviation industry partner. Reaching new heights and shattering the glass ceiling is the modus operandi for many women, and what better role models than the ladies listed. Creative, free-spirited, pioneering, and well before their time in thoughts and action. Ada Lovelace, now attributed as the first computer programmer saw beyond the automatons of her day. She saw beyond the Berullean language in front of her she was translating.  A poet father and a passion for numbers collided into her thoughts and as we marvel at AI making art, writing stories and music, and winning strategy games, we have one lady to thank. Ada. She might also be called the first Data Visualization Engineer. Don’t you think? Insightful Business Decisions are Key in Collaboration Data professionals are no longer siloed from other departments in business allowing for collaboration between teams. In partnership between both technical and non-technical employees, businesses can be sure they’re teams have a single vision to help realize business objectives and goals. The collaboration between Ada Lovelace and Charles Babbage may not have been business-related, but the ideas are the same. He passed her the document and asked her to translate, she made notes, and those notes have made history. Together they created a vision for The Analytical Machine – it exists only on paper, but it’s design, layout, and potential implementation are realized in ways unimaginable to most 100 years ago.Ada’s mathematical prowess was such that she wrote her notes in easily explainable language.She worked closely with Charles Babbage and wrote in earnest to work with Michael Farraday – she reached out to others in her field, some accepted, others didn’t. How Data Helps Inform the Future Whether you use predictive modeling, machine learning, natural language processing, or some combination of each, the data you collect helps to inform the future. We may often lament the old adage that those who don’t know their history are doomed to repeat it, but history has a shining light as well. Collaboration across the ages. Consider this. Alan Turing, the man who worked in Bletchley Park with the Enigma machine, used the notes he found to help him solve the problem. Those notes belonged to Ada Lovelace. The information she set to paper informed every stage of computer programming leading to what we know today as Artificial Intelligence. Machines that could learn and ‘think,’ not just the automatons of her age which had been ‘programmed to perform.’ The Enchantress of Numbers Known as the Enchantress of Numbers, the pioneering Ada Lovelace shares the spotlight with other pioneering women in the sciences. Think Madame Curie, Joan Clarke, even Hedy Lamarr, and of course Amelia Earhart. They weren’t of the same eras, but each of their contributions have added to what we know as the Science, Technology, Engineering, and Mathematics (STEM). We have a name for it now, but it’s always been around. And the collaborative efforts of women everywhere are growing and increasing diversity and inclusion in many businesses across the world. And at the heart of it all, in the beginning, a surprising and time-defying collaboration began. It set in motion a spark of business intelligence and insight as men and women mentored and partnered for the sake of their vision of the future. Who will be remembered one hundred years from now?  If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Karla Guerra

Karla Guerra

22. October 2020

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