There’s a lot of great jobs involving Data out there so we thought it good to share some of the great things that you can do with it.
So first of there are multiple ‘Data’ Jobs out there from Data science, Data Analysts, Data Engineers, Database managers, Data Architects and a whole host of other made-up titles. This week we are looking at Data science:
Data Scientists and Data analysts are often confused including by companies, they are in fact pretty similar and analyse large data sets often using R and Python.
Data analysts analyse data sets to better understand things that have already happened such as trends over time, for example how different marketing campaigns resulted in increased website throughput. With data scientists, however – they literally are there to try and predict the future through creating models based on big data.
Some examples of data science (and think where else it could be used to do better things if you had the knowledge to use it … just saying!)
Google: Machine-Learning for Metastasis LYNA — short for Lymph Node Assistant —accurately identified metastatic cancer 99 percent of the time using its machine-learning algorithm.
Clue: Predicting Periods The popular Clue app employs data science to forecast users’ menstrual cycles and reproductive health by tracking cycle start dates, moods, stool type, hair condition and many other metrics.
Oncora Medical: Cancer Care Recommendations Oncora’s software uses machine learning to create personalized recommendations for current cancer patients based on data from past ones.
UPS: Optimizing Package Routing Network Planning Tools (NPT), incorporates machine-learning and AI to crack challenging logistics puzzles, such as how packages should be rerouted around bad weather or service bottlenecks. NPT lets engineers simulate a variety of workarounds and pick the best ones; AI also suggests routes on its own.
StreetLight Data: Traffic Patterns, and Not Just for Cars The company’s maps inform various city planning enterprises, including commuter transit design.
Uber Eats: Delivering Food While It’s Hot In order to optimize the full delivery process, the team has to predict how every possible variable — from storms to holiday rushes — will impact traffic and cooking time.
Liverpool F.C.: Moneyball-ing Soccer built a proprietary model that calculates how every pass, run and goal attempt influences a team’s overall chance of winning. Liverpool has used it to recruit players and for general strategy.
RSPCT: Basketball-Coaching Sensor RSPCT’s shooting analysis system, adopted by NBA and college teams, relies on a sensor on a basketball hoop’s rim, whose tiny camera tracks exactly when and where the ball strikes on each basket attempt. It funnels that data to a device that displays shot details in real time and generates predictive insights.
British Olympic Rowing Team: Finding The Next Redgrave using longitudinal weight-lifting and rowing data, biomechanics data and other physiological information, they could begin to model athlete evolution.
Equivant: Data-Driven Crime Predictions Equivant’s Northpointe software suite attempts to gauge an incarcerated person’s risk of reoffending. Its algorithms predict that risk based on a questionnaire that covers the person’s employment status, education level and more.
IRS: Evading Tax Evasion Based on those profiles, the agency forecasts individual tax returns; anyone with wildly different real and forecasted returns gets flagged for auditing.
Sovrn: Automated Ad Placement Compatible with Google and Amazon’s server-to-server bidding platforms, its interface can monetize media with minimal human oversight — or, on the advertiser end, target campaigns to customers with specific intentions.
Instagram: Marketing With a Personal Touch Instagram uses data science to target its sponsored posts, which hawk everything from trendy sneakers to dubious “free watches.” The company’s data scientists pull data from Instagram as well as its owner, Facebook, which has exhaustive web-tracking infrastructure and detailed information on many users, including age and education. From there, the team crafts algorithms that convert users’ likes and comments, their usage of other apps and their web history into predictions about the products they might buy.
Airbnb: Search That Highlights Hip Areas Today, a rental gets priority in the search rankings if it’s in an area that has a high density of Airbnb bookings. There’s still breathing room for quirkiness in the algorithm, too, so cities don’t dominate towns and users can stumble on the occasional rental treehouse.
Candidate of the week
If you are interested in any of our candidates please contact us on email@example.com to discuss.
CTO (cofounder/non-cofounder), Contractor (data science/machine learning /electrical engineering), Non-executive directorships
Data Science and Machine Learning(current career): time series and image data, image processing, programming. MEng Electrical & Electronic Engineering, PhD Electrical & Electronic Engineering (power electronics: semiconductor devices, AC/DC topologies; control, 1 phase/3phase AC, and DC systems), MA(Hons)(Cantab) Law, Solicitor (England & Wales – non-practising), Chartered Tax Adviser (CTA) (non-practising): former career as a corporate tax lawyer
Legal, tax & corporate/commercial background,
Programming & Cloud (Python, Matlab/Octave, linux, AWS, data science & ML/DL packages, git version control, some C/C++)
Data science and Machine learning (data visualization, full productionisation of data science preprocessing and feature engineering pipelines, deep learning and shallow learning techniques for anomaly detection, classification, regression) based on time series and image processing data; some natural language processing experience.
Electrical Engineering (power systems fault analysis, semi-conductor device types and technologies, converter topologies, passive components, electrical transforms, power networks (AC,DC))
Jobs of the Week
These are from companies working with us and really keen to be inclusive on the gender diversity front.
They are looking for a Data Engineer to join their award-winning team. For this role, they would ideally like you to be able to commit to a minimum of 4 days per week.
Conference season is over!! Starts again in September
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Women’s Tech Hub products
Candidates page advertises the skillsets of the women we have looking for roles in the area (and some of our male allies).
Jobs Board for those wanting to advertise specifically to our members in the area – check it out here.
Engage with our members, advertise your companies, and share any jobs then you can support us by sponsoring the Workshop Wednesdays – details here.