class: center middle hide-count hide-logo background-image: url(figures/moffittlogo.png) background-size: 22% background-position: bottom 5% right 5% <div class="talk-logo swivel-horizontal"></div> <!--.talk-title[ .talk-title-main.moffitt-blue[UnicoRns are real] ]--> .talk-meta[ .talk-author[Travis Gerke, ScD] <!-- https://fontawesome.com/license --> .talk-date[<img src="figures/twitter-brands.svg" alt="Twitter logo" width="24px"/> @travisgerke] .talk-auth2[w/ Donna C. Evans] <!--Senior Compensation Consultant--> ] --- class: center inverse strive-to-recruit
.footnote.pull-right.moffitt-grey[— _Every good data science manager ever_] <style type="text/css"> @import url('https://fonts.googleapis.com/css?family=Merriweather:300'); .text-poster { font-family: 'Merriweather', serif; margin: 0 auto; } .strive-to-recruit .text-poster .line-container .line:nth-child(2) { color: #82c878; } .strive-to-recruit { background: #00589a; } </style> --- ### Parody? .w-50.h-center[ ![](figures/rasgon-tweet.png) ] --- class: inverse hide-count background-image: url('figures/enemy.gif') background-size: cover # Truth? --- ### Is there another way? .pull-left[ .center[ ![](figures/highresrollsafe.jpg) HR can't do a market salary benchmark analysis for a person that doesn't exist ] ] -- .pull-right[ .v-center[ ![](figures/dabbingunicorn.jpg) ] ] <!-- credit to vectorstock.com/22698768 --> --- layout: true class: job-posting animated fadeIn ### Data Scientist wanted! (1/2) Seeking data scientists with hands on experience transforming unique data into amazing products. You will have access to an enormous amount of high-value business activity data. You will participate in the end-to-end processes of product development using .one[machine learning], from proof of concept to .two[deploying models in production]. Your work will directly impact the developer experience in .three[building applications], as well as the customer experience when interacting with them. * Working closely with Software Engineers and Product/Technical Services Mangers to drive analysis and performance improvements * .four[Developing and implementing cloud-based security solutions] providing data protection and governance, and improving customer experience * Working with internal business teams to .five[integrate data and decision-making] * Build intelligence into our services to make them run smarter with a responsible application of Machine Learning. --- class: full --- class: job-posting-one --- class: job-posting-two --- class: job-posting-three --- class: job-posting-four --- class: job-posting-five --- layout: false ### Data Scientist wanted! (2/2) .w-85.h-center[ ![](figures/reqs.png) ] --- ### Data Scientist wanted! (2/2) .w-85.h-center[ ![](figures/reqs-hex.png) ] --- ### Challenge: job descriptions that map to appropriate salaries .pull-left[ > A common listing describes a unicorn... > These types of job descriptions usually mean the company doesn’t know what they’re looking for, and they expect a data scientist to come and solve all their problems without any support. .w-25.h-center[ ![](figures/build-career.jpg) ] ] -- .pull-right[ But unicoRns are real and should be compensated as such! .w-50.h-center[ ![](figures/unicorn_hex.png) ] ] --- ### The job description to offer pipeline -- Hiring manager writes a job description * States the primary purpose, expected deliverables * Requirements for technical skills, prior experience, and/or education -- HR classifies the role * Hourly or salary * Type of contributor: technician, professional, scientist * Level of contributor: entry, intermediate, senior, principal -- Role-specific salary benchmarking data are from purchased compensation surveys * HR will aggregate across several such sources to derive a salary range * The ultimate offer varies somewhat by company's compensation philosophy --- .panelset[ .panel[.panel-name[Data Scientist I] * Purpose: Summarize and analyze complex/large data to guide business insights * Independently merge and tidy data from multiple source systems, then conduct appropriate summarization or statistical analyses according to business stakeholder needs * Use data and visualizations to inform business solutions for organizational leaders * Organize databases, analyses, and reports into user-accessable and reproducible repositories * Preferred R stack experience: tidyverse including dbplyr, R markdown, Shiny, caret .moffitt-orange[[insert required basket of R needs here]] * May require an advanced degree * 0-2 years of related experience preferred <i>Notes:</i> * This support role reports to a manager and work is closely managed * Projects most often contain limited complexity ] .panel[.panel-name[II] * Purpose: Summarize and analyze complex/large data to guide business insights * Independently merge and tidy data from multiple source systems, then conduct appropriate summarization or statistical analyses according to business stakeholder needs * Use data and visualizations to inform business solutions for organizational leaders * Organize databases, analyses, and reports into user-accessable and reproducible repositories * Preferred R stack experience: tidyverse including dbplyr, R markdown, Shiny, caret .moffitt-orange[[insert required basket of R needs here]] * May require an advanced degree * 2-4 years of related experience typically required <i>Notes:</i> * Typically reports to a manager, though only requires occasional direction * Gains exposure to some complex tasks of the job ] .panel[.panel-name[III] * Purpose: Summarize and analyze complex/large data to guide business insights * Independently merge and tidy data from multiple source systems, then conduct appropriate summarization or statistical analyses according to business stakeholder needs * Use data and visualizations to inform business solutions for organizational leaders * Organize databases, analyses, and reports into user-accessable and reproducible repositories * Preferred R stack experience: tidyverse including dbplyr, R markdown, Shiny, caret .moffitt-orange[[insert required basket of R needs here]] * Typically requires either advanced degree or 4-7 years of related experience, or an appropriate mix of the two <i>Notes:</i> * This independent/collaborative member typically reports to a manager, but requires minimal direction * Contributes to solving complex challenges associated with the role ] .panel[.panel-name[IV] * Purpose: Summarize and analyze complex/large data to guide business insights * Independently merge and tidy data from multiple source systems, then conduct appropriate summarization or statistical analyses according to business stakeholder needs * Use data and visualizations to inform business solutions for organizational leaders * Organize databases, analyses, and reports into user-accessable and reproducible repositories * Preferred R stack experience: tidyverse including dbplyr, R markdown, Shiny, caret .moffitt-orange[[insert required basket of R needs here]] * Typically requires either advanced degree or 7+ years of related experience, or an appropriate mix of the two <i>Notes:</i> * This independent/collaborative member typically reports to a manager or head of a unit, but work is primarily independent * Often a team lead for complex problems ] .panel[.panel-name[V] * Purpose: Summarize and analyze complex/large data to guide business insights * Independently merge and tidy data from multiple source systems, then conduct appropriate summarization or statistical analyses according to business stakeholder needs * Use data and visualizations to inform business solutions for organizational leaders * Organize databases, analyses, and reports into user-accessable and reproducible repositories * Preferred R stack experience: tidyverse including dbplyr, R markdown, Shiny, caret .moffitt-orange[[insert required basket of R needs here]] * Typically requires either advanced degree or 10+ years of related experience, or an appropriate mix of the two <i>Notes:</i> * This independent/collaborative member typically reports to a manager or head of a unit, but work is autonomous * Leads teams to solving the most technical and complex problems encountered by the Data Science unit ] ] --- <img src="index_files/figure-html/unnamed-chunk-2-1.png" width="936" /> --- .map-position[
] --- ### Concluding remarks -- * Primary drivers of salary estimates are experience and autonomy + Corollary: You probably don't need to learn fancy new language X to get the job you want + These drivers may evolve in the data science domain -- * Salary surveys are not yet capturing specific data science roles + E.g. machine learning engineer, decision scientist -- * This talk is not arguing for or against the current process + Instead, it reports the pipeline that is common to large organizations to: + Empower you, the unicoRn, to capture the compensation you deserve + Empower managers to recruit and compensate the unicoRns they need --- ### MASSIVE THANKS 👏 * Donna Evans, HR guru * Jordan Creed [@jhcreed](https://twitter.com/jhcreed), unicoRn hex sticker guru * Garrick Aden-Buie [@grrrck](https://twitter.com/grrrck), `xaringanExtra` 📦 + all around CSS/JS guru * David Gohel [@DavidGohel](https://twitter.com/DavidGohel), [`ggiraph`](https://davidgohel.github.io/ggiraph/index.html) 📦 * Tampa R Users Group [@UseRTampa](https://twitter.com/UseRTampa/), the feedback gurus * [Emily Robinson](https://twitter.com/robinson_es) & [Jacqueline Nolis](https://twitter.com/skyetetra), gurus of writing the [bestbook.cool](https://www.bestbook.cool) 💻 https://github.com/tgerke/unicoRns-are-real <br> 📺 https://unicorns-are-real.netlify.com/ <br> <img src="figures/twitter-brands.svg" alt="Twitter logo" width="24px"/> [@travisgerke](https://twitter.com/travisgerke) .w-15.h-center[ ![](figures/unicorn_hex.png) ] <style type="text/css"> .talk-logo { width: 480px; height: 556px; position: absolute; top: 5%; left: calc(50% - 240px); background-image: url('figures/unicorn_hex_title.png'); background-size: cover; background-repeat: no-repeat; } .talk-title { font-family: Overpass; } .talk-title .talk-title-main { font-size: 2.3em; font-weight: bold; position: absolute; top: 55%; left: 0; width: 100%; } .talk-title .talk-title-sub { font-size: 1.28em; position: absolute; top: 66%; width: 100%; left: 0; } .talk-meta { font-family: Overpass; position: absolute; text-align: left; bottom: 25px; left: 35px; } .talk-meta p { margin-top: 0.25em; margin-bottom: 0.25em; } .talk-title { margin-bottom: 5em; text-align: center; } .talk-author { color: #444; font-weight: bold; font-size: 1.5em; line-height: 1em; margin-bottom: 0; } .talk-date { color: #666; font-size: 1.25em; line-height: 0; margin-top: 0; } .talk-auth2 { color: #666; font-size: 1em; line-height: 0; margin-top: 0; } .hide-count .remark-slide-number { display: none; } @keyframes swivel-horizontal { 0% { transform: rotateY(0); } 50% { transform: rotateY(360deg); } 100% { transform: rotateY(360deg); } } .remark-visible .swivel-horizontal { animation-name: swivel-horizontal; animation-duration: 5s; animation-timing-function: linear; animation-iteration-count: infinite; } .moffitt-orange { color: #faa555; } .w-15 { width: 15%; } .w-25 { width: 25%; } .w-50 { width: 50%; } .w-85 { width: 85%; } .h-center { margin: 0 auto; } .v-center { display: flex; justify-content: center; align-items: center; } .job-posting:not(.full) { color: #aaa; } .job-posting-one .one, .job-posting-two .two, .job-posting-three .three, .job-posting-four .four, .job-posting-five .five { color: #eb1455; } .map-position { position: absolute; top: -20%; width: 100%; left: 0; } </style>