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Handbook

This handbook demystifies the nuances of job searching by laying out everything you need to know. You’ll find checklists, do’s and don’ts, templates, DS social media advice, external resource links, and advice for every step of your search.

In it, you’ll find resources on:

Your one-stop resource for DS job search information, careers requirements, and tips.

Data Science Careers

Some of the companies Lambda School DS graduates work at:

Resumes

So you know how to stand out in your field and make a stellar first impression

Interviewing

So you can highlight your strengths and accomplishments in the most impressive way possible

Applying

So you can convince any employer you’re someone they want to know

Networking

So you can learn about your field, get a foot in the door, and find mentorship in your field

Negotiating

So you can secure offers that respect your value as a candidate and allow you to grow your wealth

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Contents

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Before the job search

Before you start your job search, make sure you have done all of the following so you’re ready to put your best foot forward.

Ensure all your documents and artifacts are ready-to-ship.

This includes:

  • Resume

Find DS specific resume requirements here.

  • LinkedIn

Getting set-up? LinkedIn deep dive available here. LinkedIn can match and expand further what’s on your resume.

  • Online presence: portfolio and/or blog

Data Science students should have a blog, website, or other long-form written description of your projects with visuals.

  • GitHub

Prepared with the most impressive projects in your top 3. Keep it active daily to keep your graph green.

  • Social Media

If using for your search, remove any unprofessional content and post regularly about topics related to Data Science. For personal accounts, make them private as employers typically search for candidates on Google and other platforms.

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Professional Endorsement

By the time you finish Labs, your career materials should be prepared to be reviewed for “endorsement” by a career coach or coordinator. Professional endorsement means you have completed all requisite career materials (see below). Full endorsement encompasses passing technical assessments as well. Once you earn your professional endorsement, along with your technical endorsement, you will gain access to our pipeline of hiring partners.

For more in-depth information: Careers Endorsement Handbook here.

CHECKLIST FOR ARTIFACTS NEEDED FOR DS PROFESSIONAL ENDORSEMENT:

One page resume featuring:

“Skills” section with all the technologies and platforms you know

“Projects” section that highlights your data science skills and knowledge

“Employment” section with power statements for transferable skills from past jobs

“Education” section featuring Lambda School and previous schooling

Updated LinkedIn (LI) profile, including:

❏ A clear headshot and cover photo

Personal summary in the About section to let people get to know you. Include your technical skill section from your resume here

Work experiences, with descriptions

Projects, which LI categorizes under “accomplishments”. Highlight personal, build week, and labs projects, with a link for any deployed projects or code repos

Education, featuring Lambda School and any previous schooling

Green GitHub with quality contributions, including:

❏ Clear headshot and and professional user handle

3 Pinned projects, should include open source contributions, and/or Build Week or Labs projects

Weekly contributions, to show ongoing commitment to skills-building

Active online presence, including a portfolio site (buildable through Beautiful Jekyll, Wix, Squarespace, etc.) OR Medium/other blog highlighting projects and skills, including:

❏ At least 2 posts or long-form writing describing your projects and technical learning

❏ Links to LinkedIn, GitHub and other relevant artifacts

❏ Links to polished Build Weeks and Labs projects

OTHER STEPS TO EARN YOUR CAREERS ENDORSEMENT:

Behavioral interview & Technical DS Interview (combined) with CoGrammar

Social media and other online presence (if used) is relevant and professional

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Applying to Lambda Partners

Lambda School's Solutions team works diligently to create leads for students by forming relationships with hiring partners. Partners are companies that have hired or are excited to interview and hire Lambda students. Once endorsed, you'll be able to utilize this resource to assist in your job search and help represent Lambda!

  • Gain eligibility

You’ll work with a Careers team member and Hiring/Solutions team member to ensure you’re up to speed on your careers materials and preparation for the interviews that will be scheduled for you.

  • Be an ambassador

Many companies are curious to know what Lambda grads are all about; show them what you and your peers can do by communicating thoroughly, preparing well for interviews, and asking for help from a coach or member of the solutions team when you need it. You will help pave the way for future DS grads to access more field related opportunities!

  • Keep Lambda in the loop

Have an interview? No longer interested? Unsure about how to proceed? Got an offer? Let Lambda know by messaging your coach or coming to Office Hours.

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Networking

Whether it’s cold outreach, attending a tech talk or webinar, hackathon, speed networking, hiring fair, or any other number of interactions that connect you to others in the field, know what you need to make a memorable impression

Networking event tips:

  • Research presenters and/or attendees

Some events release the attendee list ahead of time; if so, try to find people with whom you share an interest and strategically strike up a conversation with them at the event. Otherwise, research the speakers, presenters and organizers to develop a strategy and points of conversation.

  • Ready your pitch

You’ll have many opportunities to introduce yourself to new people, so ensure you have a 30-second pitch that highlights your background, strengths and interests. Check out these templates to get started.

  • Prepare conversation-starters

Especially good for nervous networkers, having some pre-packaged conversation starters can alleviate awkward silences. Find some ideas here.

  • Print resume copies

You may not need hard copies or either, but it’s a good idea to have them on hand if someone asks how to get in contact with you.

  • Research

Especially for tech talks or other events that have a topic or theme, doing advance research can help you talk the talk, and start informed during conversations with other attendees.

  • Follow up with the people you meet

Send a follow-up email to anyone you meet within 24 hours of the event. Pro-tip: Subtly jot down notes after you talk to each person so you can remember who’s who the next day. Find email templates here.

Networking continued on next page....

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Networking with the Virtual

DS Community

Growing a network takes time and consistent effort in engaging with the data science community. You can begin to build connections online through platforms like Medium, Twitter and LinkedIn.

Follow these Data Science leaders on social media and take note of who follows, engages with or likes their content:

Data Science Focus:

Data Visualization Focus:

Sign up for these newsletters to stay on top of trends in the DS space + Get job postings in your inbox

Data Science Central ML Jobs Newsletter

Kaggle News AngelList Blog

Women Who Code OpenAI

DeepMind Microsoft AI

Salesforce AI Research StitchFix Tech Blog

Towards Data Science Nature Machine Intelligence

LinkedIn Groups:

Machine Learning & Data Science

Women in Machine Learning & Data Science

Women in Data Science

Python Developers Community

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Twitter Topics:

Machine Learning

Data Science

Artificial Intelligence

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Informational Interviews

Informational interviews are one of the lowest-stress, highest-impact forms of networking. They are when you invite a professional who works in the field or company you are trying to break into to have a casual conversation about their knowledge and experiences.

  • Identify people to meet with

Whenever possible, start with your warm contacts to get an introduction to new people, but you can also message cold to ask for an introduction! Focus on anyone who works in your goal job, or at a goal company.

Find networking how-to’s here, email outreach templates here, and LinkedIn templates here.

  • Research the person before you meet

Review their LinkedIn to learn more about their background.

  • Prepare questions ahead of time

While you want to let the conversation flow naturally, you also want to be prepared with some questions to kick things off. Remember, this is your opportunity to learn, so take advantage of it

  • Ask for recommendations

Don’t leave an informational interview without asking, “is there anyone whom you’d recommend I speak with to learn more about X field?” or “what next steps would you recommend for someone interested in X field?”

  • Send a thank you email

Just like in interviews, don’t let this one slip! Templates here.

  • Do not ask for a job

Informational interviews are your chance to learn, and are not the right time to ask for a job. Continue to foster the relationship, and later on the person may be willing to be a reference.

  • Stay in touch

Don’t let the person forget about you; keep them posted on your progress.

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Resume checklist (Page 1 of 2)

Data science resumes tend to be visually simple and traditional, with the projects section being the centerpiece. As you develop your resume, follow along with this checklist to avoid common errors:

Your resume should have all the following components in this order of priority:

  • Name header and contact info. Include a professional phone number, your city/state and an email. Link to other relevant sites like your github, LinkedIn, and blog/portfolio.
  • Summary (optional). This can be used to describe your top skills and accomplishments, along with connecting skills from previous experiences to what you do now. Focus this area on answering What makes me unique? or What do I bring to the table?
  • Skills sections, separated by skill set and technology type (if needed). Examples subsections forDS skills: Languages, Packages, Pipelines or Dashboards, Machine Learning, Tools, Analytics, Statistics and Mathematics, Computer Science
  • Project section, formatted in such a way that highlights your contribution and use of different skills or technologies to bring the project to completion.

Project Name, Link (link to Github Repo or Front End), Year

    • First bullet point describes the large goal/accomplishment of the project. Start all bullets with a past tense verbs. Ex. Built a recommendation system for people to find TV shows across platforms that align with their interest types.
    • Second & third bullets should describe what YOU did on the project and include all technical details. Ex. Created pipeline using ____ to feed into _______.

  • Employment or experience section. This section focuses on using bullets to highlight transferable skills, noteworthy accomplishments and responsibilities. When applicable, emphasize how you used data to make decisions or relevant technical tools in previous roles.
  • Education section, list Lambda School with “Data Science” highlighted as your studied track. Include any previous schooling from other institutions or entities. If you have any certifications and training you’d like to highlight, rename this section “Education and Training”.

Resume checklist continued on next page…

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Resume checklist (Page 2 of 2)

Resumes follow a few rules of thumb for formatting, these include:

  • Writing bullets in the form of power statements, starting with an action verb and include quantifiers/qualifiers and results. For example:
  • Analyzed results of user experience survey to identify trends or patterns
  • Use of “disembodied first person”, eliminating use of “I” or “my” across resume

Instead of writing: “I was responsible for authoring a report for my team, summarizing the results of the data we collected”, write: “Authored report to present to team, summarizing results of collected data”

  • Font size is minimally 10.5 pt and clean (calibri, helvetica, etc.)
  • Date, bullet, heading, etc. formatting are all consistent
  • Colors or graphics are not distracting
  • One page in length (with few exceptions)
  • No headshot or full street address included (only need city/state)

To see a real DS resume check out these two Lambda School Data Science Resume Samples. Additionally, you can find Lambda’s resume deep dive here, featuring general resume tips.

For extra resources on DS resumes check out the following articles:

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Tailoring a resume, cover letter, or interview prepping

Every job is different, and to really stand out, you’ll need to tailor your approach. You don’t need to start from scratch for each job, but you should not send the same application or give the same answers for every job you are going after.

  • Keep a master version of everything

There will be transferable components in your interview responses/ resume/cover letter. Keep a master copy of everything that you can duplicate and work off of when tailoring your apps.

  • Find the most important aspects

Go through the job description and highlight any tools or responsibilities mentioned multiple times throughout the posting, as well as any mentioned in the first couple bullets. These are likely to be most important for the role.

  • Identify your strengths

For the most important skills, know which ones you’re strong in, and how the company expects you to use those skills.

  • Brush up on your gaps

Practice anything in the description that you’re rusty in, or check out free online courses to build a foundational understanding of any new skills. You don’t need to be a pro at 100% of the skills listed, but you should be able to speak to them intelligently.

  • Write 5-8 relevant stories that highlight your core skills

You should be able to tell a story in response to any aspect of the job description that highlights your experience with something similar. These don’t necessarily have to be impressive examples; the important thing is that your transferable experience is evident.

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Before an interview

Anytime you have an interview, plan to spend at least twice the duration of the interview preparing. I.e., for an hour-long interview, prep for at least 2 hours.

  • Research the company

Know their products, history, and any recent news. Familiarize yourself with their culture so you know what to wear and how casual/formal it is.

  • Research your interviewers

Learn a bit about each of your interviewers via LinkedIn. Not sure whom you’re meeting with? Ask the person who set up your interview for names.

  • Map out the job description and practice answers

Go through the description and highlight the expectations. Make sure you have at least one story to highlight your experience with all of the experiences. Practice your answers and tailor them to the job/ company. Find more on prepping STAR stories here.

  • Know your value

Salary may come up as early as the first conversation with a company; be prepared for this question by researching ranges on Glassdoor. More resources to prepare for this conversation here.

  • Brush up on your skills

Be ready to get grilled on any of the technical skills in the description. Set aside time to practice both your skills and talking about them. For skills you lack, do research so you can at least speak to them with confidence.

Find more on prepping for technical interviews here and here.

For Data Science Specific Interview Prep Resources:

  • Prepare questions for your interviewers

Always bring at least 2-3 questions! But don’t ask things you could easily Google for yourself. Find some ideas here.

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In an interview

Impressions matter! Most interviewers decide within the first minute of meeting someone whether they may want to hire them, so be ready to impress

  • Don’t arrive too early

If you prepared for Murphy’s Law, you should arrive at least 10-15 minutes before your interview. Any more than 15 minutes, wait in your car or a local coffee shop. You want to seem organized, not desperate.

  • Throw out your Red Bull, take off your headphones

Having a water bottle or cup of coffee/tea is fine, but chuck the soda, energy drink, or gatorade (or put it in an opaque water bottle). Take your headphones off before you enter the building, and tuck your phone away so your attention is clearly 100% focused on the company.

  • Smile, make eye contact, and give a firm handshake

This is key when meeting people for the first time, and will help you project confidence, even if you’re filled with butterflies.

  • Treat the front desk staff well

Many interviewers ask staff whether the interviewee treated them with respect; being nervous isn’t an excuse for blowing off the receptionist!

  • Mirror the interviewer

Want to seem comfortable, like you already fit in at the company? Look at your interviewer’s posture and body language and mirror it.

  • Don’t get too comfortable

It’s ok to loosen up a bit, but keep your professionalism on point! You’re still being evaluated in relaxed interviews, casual lunches, or happy hours.

  • Take notes

Jot down anything relevant or interesting your interviewer says so you can incorporate it into a future answer. Are they struggling with something you know how to automate? Slip that in later on in another answer!

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After the interview

Your interview doesn’t end once you leave the building; there are key next steps that you can and should take to keep yourself top of mind.

  • Send a thank you email within 24 hours afterwards

Do not miss this step! It takes less than five minutes and can make the difference between you and another candidate, plus it keeps you fresh in your interviewers’ memories. Find a template here.

  • Follow up regularly

Don’t wait for the company to reach out to you; check in once per week with the recruiter/point-person coordinating your interview process to stay top of mind, and to reaffirm your interest in the role.

  • Check your email and phone regularly

Don’t ghost on a company at any stage in the process; make sure you add their domain to your safe senders list and respond to any messages within 24 hours.

  • Be prepared

You might be invited for another interview on short notice; review the description regularly so it doesn’t slip from your memory, and keep brushing up on skills you may need for an interview (chances are, this won’t be the only job you’ll need them for anyway!)

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Negotiating an offer

Negotiations can be intimidating, but they’re an expected part of the offer process. Remember, earning potential compounds with age, so don’t miss the chance to increase yours!

  • Let Lambda know!

Reach out to Lambda when you get an offer (Courtney Untiedt is your point of contact!) so we can help you negotiate and consider your options.

  • Know your value

Research the market value for your position before your first conversation with the company; Glassdoor and PayScale should be your first resources for this. Be prepared to answer salary questions in the phone screen.

  • Always negotiate

You’ll never lose an offer for negotiating professionally and within a reasonable range for your role. Even if an offer seems great, negotiate!

  • Prepare for different conversations

It might not go as planned; prepare plan b and c ahead of time. Sample scripts can be found here.

  • Everything is negotiable

Maybe they can’t budge on pay, but can they budge on equity? PTO? Flexible hours? Education reimbursement? Your entire compensation package is negotiable.

  • Get it in writing

Do not sign anything until it has your agreed-upon compensation (negotiations included) in writing.

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Declining an offer

You never have to accept an offer, and there are ways to graciously decline that still keep you in that company’s good graces. You never know if there will be future opportunities you’ll want!

  • Communicate

The most important thing is to never ghost on a company at any stage. Find templates here for withdrawing professionally.

  • Express gratitude

Companies spend a lot of resources (money and time) to interview each candidate; make sure they know that you appreciate their time and consideration.

  • Keep Lambda School in the loop

If you’re interviewing with a partner, make sure you let Lambda School know so we are aware why you’re declining; your reason may be relevant to other students.

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Accepting an offer

So you got the offer you’ve been dreaming of; congrats! Before, during, and after the acceptance process, make sure you do the following so you’re not missing key steps.

  • Talk to a coach!

We want to help you negotiate, evaluate your options, and feel great about your offer. Before you accept, reach out to a coach to discuss it.

  • Make sure it’s what you want

It is not good to accept an offer and later rescind it, even before you have started. If you are still interviewing with another company and need more time, work with a career coach to ask for this so you can take the right next steps. Find tips for considering offers here.

  • Negotiate!

See here for tips on negotiations. The most important thing is to always negotiate! Unless the company explicitly told you they don’t negotiate up front, assume it’s an expected part of the process.

  • Get it in writing

Nothing is final until it’s in writing and you have signed an official offer. Read this document well before signing to make sure you understand it.

  • Let Lambda School know

Whether your offer is with a partner or with a company you found on your own, we want to hear about it! Message Courtney Untiedt, and take a selfie with your offer letter and post in the #hired channel- you deserve to brag!

  • Let other companies know

If you’re interviewing with other companies, tell them that you have accepted an offer elsewhere. Find templates for this here.

  • Be mindful of how you share the news elsewhere

Feel free to share an update on your social media or LinkedIn, as long as this isn’t violating your contract, but avoid saying anything negative about the company, sharing details of the interview process, or publicizing other company details.

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First three months on the job

While securing an offer is a major milestone that you should celebrate, now is not the time to relax or tone down the hard work! Think of the first three months on the job as an extended interview; this is a critical period for you to cement your place in the company.

  • Ask lots of questions, but not the same one twice

You’re not expected to know everything; ask questions to make sure you understand expectations well, and take detailed notes so you don’t need to ask the same thing again.

  • Get to know the team

Being the new kid on the block is the perfect excuse to schedule 1:1’s with people on the team to get to know them and what they do. Don’t be shy- strong relationships will help you down the road!

  • Use 1:1’s wisely

You should have a 1:1 with your manager every 1-3 weeks; if you don’t, ask your manager if you can schedule this. Use this time to share progress updates, confirm priorities, and ask for feedback.

  • Don’t get too comfortable

Even if other people on the team roll up at 10am, play foosball for an hour every day, and drink liberally at happy hours, that doesn’t mean you should, too.

  • Take new things on and go above and beyond

Is there a project nobody else wants to do? A system you know you could improve? An awesome new idea you want to introduce? Go for it and own it- just make sure you communicate to any key stakeholders.

  • Document everything

Track all your goals, tasks, and accomplishments. This will help you prepare for performance evals (usually 3-6 months after starting)

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Resource Center

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Supplemental resource links

Resumes and LinkedIn

Professional endorsement requirements

  • Data science

General interviewing preparation

Salary negotiations

Data science resources

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Supplemental resource links (cont.)

Application Organizers

  • Huntr
  • Job search tool

DS boards

  • BigDataJobs
  • Kaggle
  • DS Central

General job boards

Remote/relocation boards

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Supplemental resource links (cont.)

General

Interview practice

  • Pramp (free peer-to-peer interview practice)
  • Interviewing.io
  • LeetCode

Networking resources

Templates

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