an interview with Alice Genevois, senior data science manager at Lloyds Banking Group
Alice Genevois, senior manager of data science at Lloyds Banking Group, continued her education with her eye on a career in marketing and discovered in the process a love for data that eventually shaped her career beyond what ‘she had been able to initially imagine and pave the way for a career in the thriving field of data science.
“I thought when I was younger I would go into marketing. I did a double degree and I did a master’s degree in marketing and business analysis. When I started to do a bit of both, I realized that I really like numbers, I like data. I liked marketing because I know how to talk to people and stakeholders, but actually it’s the data, it’s having the facts and the numbers behind you. I like having a yes or no answer, and only the data can really give that to you. ”
Right now, every organization is in a race to monetize the colossal amounts of data they have. Those without strong data strategies are being left behind as the pace of digitization accelerates. Data science fuels these strategies, but it’s a complex field, made up of the overlap of several disciplines such as data analytics, machine learning, and algorithms.
Data scientists are a much sought-after resource because they combine math, coding, and analytical skills with an ability to communicate their findings to business stakeholders.
After leaving academia, Genevois began working in business consulting where she worked for four years using data analysis and modeling to provide financial services clients with insight into where and where. how the opportunities could be exploited. In 2017, a stint at BT came – and one of the moments in his career that Genevois is rightly proud of.
I had a lot of high level knowledge but if you asked me to write a line of code I probably couldn’t
“When I left the board I had a lot of high level knowledge, but if you asked me to write a line of code I probably couldn’t have. I had done a bit of training, but applied for this role at BT knowing that I didn’t have one of the key skills to be a data analyst, which was code – it was SQL at the time.
“Even though SQL was one of the key requirements in the job specification, I was able in the interview to show them that I can learn and that I want to learn. They hired me then trained me and within a few months I was delivering. stuff for them. “
By the time Genevois left BT, she was providing complex data analytics and strategic insights, mastering SQL among other data tools and leading their consumer measurement framework program, which involved multiple project streams across the board. business.
the Festival of Women and Technology in the World 2021 takes place in November. Sign up today!
It was also at BT that Genevois began to get involved in mentoring and coaching others as well as promoting volunteer opportunities throughout the company.
In 2019, a shift to Lloyds Banking Group called – and with it a shift to data science. Genevois led several analysis and data science projects for 17 months before winning a promotion to a senior executive position.
“Now, I lead several teams, mainly on data governance, risks and the effective use of models”, she explains.
Genevois is undoubtedly confident in her abilities and what she could bring to the senior management level, but admits to feeling a little disheartened by the lack of women at the senior management level – even though she struggles to stress that this was not discrimination on the part of Lloyds. this has led to the disparity.
“At the senior management level, there was only one other woman out of 15. I know Lloyds didn’t discriminate against women, but when there are so few role models, you wonder. if it’s really achievable. Now there are two of us. hoping it encourages more women! “
Le Genevois does much more to encourage the progression of women in data than just hope. In addition to being involved in the Women and Technology Excellence Awards, she is one of the main members of the Women ConnecTech network of the Lloyds Banking Group, through which she co-founded the Coach to Code program which brings together women who want to know more on the data. and coding with coaches to provide advice, training and inspiration. When asked what advice she gives to women starting out in technology careers, Genevois stresses the importance of mentoring.
Getting a mentor will really help you in your career
“Getting a mentor will really help you in your career. Your supervisor is not the same thing, he will focus on your current career and what you are trying to do right now. The mentor helps you to really realize your main strengths. . are. By asking you the right questions, they help you understand what you really want to do. This might be the path you’re on, maybe it’s a different path, but like the mentors are very high level, they could introduce you to more people and help you start to build your network. ”
Genevois also stresses the importance of mentoring others, even relatively early in your career.
“As soon as you feel confident then find a mentee. You will always have at least a year more experience than anyone else and you may want to pass that experience on and on. what network of women in your company or on LinkedIn. Be among the women who clearly shoot in the right positive frame of mind. ”
Genevois is a shining example of what data science can offer as a career, but also what confidence looks like. The level of chutzpah demonstrated by standing for a role for which she was only partially qualified, stands out as a scathing response to those who argue that part of the reason for the shortage of women in leadership roles is that ‘they are naturally more reluctant. and reluctant to come forward for them.
See also: Women in Tech: Confidence Isn’t the Issue
“I think some of the promotions I’ve had in the past have happened because in every meeting I would say I hit all of my goals, did this, when did I get promoted? and again, until I figured it out, because I think it’s like anything else, unfortunately, unless you ask, you don’t will not get. “
This refreshing and unambiguous approach is reflected in the approach Genevois adopts in his work.
“I find the data peaceful. There’s a lot of information out there, you figure out what you need to get out of it, you make your model, and then that gives you an answer. It’s kind of final – and I like this.”