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Why you need a martial arts approach to your #datacareer Dânia Meira (she/her) October 2022

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Agenda Intro 01 03 Q&A 04 02 #datacareer opportunities #datacareer progression Dânia Meira (she/her) October 2022

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Companies like LinkedIn, Google, Hubspot are now offering corporate BJJ sessions as part of their free health and wellness packages. Source: https://davra.com/jiu-jitsu-is-eating-the-software-developer-community/ Intro 01/03 Dânia Meira (she/her) October 2022

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Dânia Meira Director #datalift and founding member at AI Guild #datacareer since 2012 Former Bootcamp teacher Brazilian Jiu-Jitsu purple belt at Gracie Academy Berlin #BJJ practitioner since 2017 Self-defense workshop lead Intro 02/03 Dânia Meira (she/her) October 2022

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My #datacareer journey BsC Applied Math Marketing Analyst MsC Computer Science Data Scientist (BR) Data Scientist (DE) Teaching at Data Science Bootcamp Founding member and Director #datalift Intro 03/03 2007-2011 2012 - 2014 2014 - 2015 2014 - 2015 2015 - 2020 2019 - today 2017 - 2020 Dânia Meira (she/her) October 2022

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Parallel between Data Science and MMA #datacareer opportunities #datacareer opportunities 01/04 Dânia Meira (she/her) October 2022

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#datacareer opportunities 02/04 Data Science in Production Dânia Meira (she/her) October 2022

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MMA: Mixed Martial Arts Full-contact combat sport that allows the use of various martial arts both standing (striking) and on the ground (grappling) It promotes the use of a wide variety of fighting techniques and skills to be used in competition It requires the person to learn multiple types of fighting styles from distinct combat sports Image credit: Reinhold Matay-USA TODAY Sports #datacareer opportunities 03/04 Dânia Meira (she/her) October 2022

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Data Science is a team sport #datacareer opportunities 04/04 While for MMA, one person is the figher that dominates various techniques Dânia Meira (she/her) October 2022

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Parallel between Seniority levels and BJJ ranking system #datacareer progression #datacareer progression 01/05 Dânia Meira (she/her) October 2022

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Analyzing the Analyzers (2013) Sean Murphy, Mark Vaisman, Harlan Harris The most successful practitioners are those with substantial, deep expertise in at least one aspect. Mean Skill Group loadings for survey participants categorized into four Self-ID groups #datacareer progression 02/05 Dânia Meira (she/her) October 2022

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The BJJ ranking system Different colored belts signify increasing levels of technical knowledge and practical skill It contains many of its own unique aspects, like a marked informality in promotional criteria The average time frame to become a black belt is around 10 years with a consistent training schedule Source: https://ibjjf.com/graduation-system #datacareer progression 03/05 Dânia Meira (she/her) October 2022

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Seniority levels in #datacareer Despite being around for over a decade, Data Science is still not a very clearly defined field Many companies don’t really know what they want from their Data Science team Building smart data products requires deliberate practice for many years Even after more than 10 years, you don’t know what to expect out there, what new trends will emerge and where the market will go #datacareer progression 04/05 Image credits: Christina Morillo on Pexels Dânia Meira (she/her) October 2022

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Sometimes it is just a promotion Companies worth working for can show you the career path for the relevant data roles Practitioners have provided the basic framework What is the Senior level? #datacareer progression 05/05 The AI Guild has you covered from entry-level to lead and CxO Dânia Meira (she/her) October 2022

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Accreditation of experts Competency profiles for the Senior Level Talent CV validation and career support https://datacareer.theguild.ai #datacareer Dânia Meira (she/her) October 2022

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Like martial arts, data science has a philosophy Just as no martial artist is trained to attack the innocent, your skills come with a responsibility and have to be applied with care and due diligence The ethical aspect of working with data, in particular privacy concerns, biases of machine learning models Dânia Meira (she/her) October 2022

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Questions? Dânia Meira (she/her) October 2022

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Competency profile Some examples from AI Guild members. Computer Vision engineer, Data Analyst, Data Scientist, Deep Learning engineer, Data Engineer, Machine Learning engineer.

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I am a Machine Learning engineer (e.g TF, Scikit) with extensive industrial experience. Previously, I focused on data analysis, including time-series predictions (Numpy, Scipy) with a large impact on aircraft maintenance cost. Based on project management and team building expertise, I lead the end-to-end delivery of ML-based solutions. Data Analytics Timeseries Machine Learning ML Ops 5+ years business innovation and technical leadership. Ten times: Pipeline building and model optimization for forecasting aircraft noise from 25k flights (e.g. Pandas, Numpy, Scipy, Plotly, Hadoop, Spark). Ongoing 6m+: Generative design of DL surrogate model for stress and loads from airframe data. Model building accelerated by 10x. Test-driven model monitoring (e.g. SageMaker, MLflow).

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I am a customer-centric data analyst capable of fast iteration for better business solutions. For example, I have led project teams exploiting niches in the automotive value chain with new technologies and products. My strong suit is working with technical teams, as I have 5+ years of experience in advanced analytics and modeling (Python, R, SQL). Experimental method Predictive modeling Data Analytics Business innovation Classification and Regression models, Time Series, CNN, Computer Vision. 5+ instances of utilizing analytics for market, competitor analysis, and strategy adjustment to incubate disruptive ideas. Done twice: From customer behavior and segmentation to a data-driven approach for building new products and value chains. Ph.D. in experimental nanophysics (10- 11 millibar, -272 ℃).

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Thank you! Join our AI Guild community at www.theguild.ai