Starting work is the next step in your learning journey. It is through work that you will learn the most about your chosen field.
- Starting work is the next step in your learning journey. Your goal is to find a job that pays you, allows you to learn, connects you to others that you can teach/learn from and which allows you career progression opportunities.
- Understanding what your career options are and what possible career progress pathways are
- What types of contracts are possible
- How to get your first job
- How to getGetting your first job.
- Planning out your career, 2 years and 5 years out.
- Understanding the salary market.
- Resume/Cover Letters
- How to do remote work well
Data Science is full of different terms including <Data Science, Data Engineer, Machine Learning Engineer, NLP Engineer, ...> How do all of these fit together?
One resource that explain this well is IamAI roadmap
- As part of understanding what role you will take up, you must also decide which roles you will not pursue.
- When you apply for jobs.
- When you make your 2 year career plan
- When you put together your application profile
- When you do your monthly/annual reviews with your employer.
We think that you're here because you want to work in industry. Academia can be wonderful and so can entrepreneurship, but we believe that the majority of impact that's made in the world is made through those employed in work. This overview should help you to understand how to launch your career with a special view of remote work, which is becoming increasingly common-place.
While we have designed 10 Academy such that you will pick up the competencies that you will need to be job-ready, it's important for you to understand what the employer side of the job market expects from employees so that you can maximize how far and how fast you can go.
All of this starts the transition from university to your first job.
Our goals are threefold:
- Place trainees into jobs quickly (target 3-6 months post 10 Academy)
- Place trainees into good jobs that harness the trainees' potential (where trainees are learning while contributing)
- Place trainees into well paid jobs (targeting twice the average of non-10 Academy graduates from one's university)
- Full-time regular (may be remote)
- Analogy: Long-term stable relationship. A commitment is made from both parties to work together and stability provides a place to grow.
- Jobs advertised publicly and likely the longest vetting process.
- The expectation is that you will be with the company for a period with no fixed end-date in mind. This allows the company to depend on you and for you to depend on the company.
- There is a cancellation notice period from either side - usually 4-12 weeks
- This is likely the only possible way for you to get stock options with a company - they don't come without investing something significant into the company, either money or quite a lot of time.
- You would likely get benefits from the company.
- Full-time fixed duration contract (may be remote)
- Analogy: Stable relationship while doing a PhD - while you are there, you know that you will make it work, but there is always an end-date in mind. Stability and growth is there, though very long-term planning may not happen.
- Jobs may be advertised publicly, probably a long vetting process.
- Both you and the company invest in the other, and continue to extend the contract on a regular basis as needed.
- This is a popular model for stable remote work.
- You may get some benefits from the company.
- You are unlikely to get any stock options.
- Contract
- Analogy: Summer romance
- You are hired to deliver a specific task within a certain amount of time. There is not necessarily an expectation that you are part of regular team meetings and you may be working on items which are outside the regular company workflow.
- Jobs may be advertised, but will often accrue through contacts and networks.
- Contracts likely in the 3-6 month timeframe.
- You are highly unlikely to get any benefits from the company or stock options.
- It's very important to make the expectations clear - most contracts will not have this 100% clear at the start, and this is important to clarify - what has to be delivered by when, and when payments are made.
- Freelance
- Upwork etc - not covered here.
Understanding which type of job you want to go for - this must be one which actually exists and which is hiring for people with your experience level. 10 Academy is currently training for Machine Learning Engineer and Data Engineer roles.
If you are here, we are assuming that you are interested in a career in Data Science and, more specfically as either a Machine Learning Engineer or as a Data Engineer. Great, now how to get started in finding roles that are open?
Your goal is here not to find jobs that you want to apply for, yet - rather, you want to develop your own understanding of what industry is looking for. A career means that you are doing a job for someone else, and you need to develop an understanding of that 'someone else' is looking for. An analogy here is if you are selling airtime to university students. Before you can effectively sell, you need to figure out a) what airtime packages students want to buy b) how much they are willing to pay c) where do students go to buy airtime. To be able to sell, you need to understand what your customers are willing to pay for. To be able to sell, your customers must also have a need for airtime.
It's important to approach this in a systematic fashion. How to gather information?
- Talk to people in your network
- 10 Academy careers placement
- 10 Academy alumni
- Your university alumni networks
- Contract and job search sites
We don't provide a format for information collection, yet, but you should be able to define some/most of the following items for your chosen field.
- Links to 5 real jobs that are advertised anywhere in the world that you could take up
- Links to 5 real people who are at 2nd degree connections on LinkedIn who are working at companies hiring for roles that you want
- A clear list of requirements for the job that you want to take up. This should focus on what skills employers are looking for.
- A salary range for the job you want to take up.
This will be a living document. Consider doing this study with a partner or a team.
An idea of what the career trajectory along your chosen path looks like. What is the 'next job' that you want to go for after you get started, and who (outside of FAANGs) are hiring for these roles.
When you get to this stage, it is believed that you have some work experience in a field that interest you and you want to move to the next job. You have to plan ahead, ask yourself questions like "what role can i take", "what are the companies hiring looking for", "how does this new role help me attain my career goals", "what are the commitment involved" etc provides answers to each questions and that will help you take the next step.
A profile site that showcases your past projects, your CV, your contact information and which links to your codebase
CVs are a start, but they are incomplete. We will provide you with a template to fill in which includes contact information, your CV, link to your GitHub and allows you to showcase projects which are relevant to your chosen choice of career. This is a CV+ and we've found that employers prefer this to just a CV.
Having a good CV is a necessary but not sufficient condition to start your career. It's an imperfect system, some say that it promotes exaggeration and there are many (fair) charges that can be laid against the use of CVs - that being said, it remains a global standard.
Your CV for the purposes of work should always be:
- No longer than 2 pages
- Use a single font (bold, underline, spacing, different sizes all OK)
- Free of any spelling errors
- Free of weird formatting
- Formatted for an international audience
- Do add country codes to phone numbers, add countries to work, write out terms so that they are globally understandable
- Do not use acronyms that non-nationals may not understand (JKUAT may not be understood outside Kenya)
- An honest reflection of what you've done in the past
- Each of your CV entries should follow Bock's formula which he explains here
- Only send PDFs
- Name your file with your name
- Be ready to tailor aspects of your CV to the job that you are applying for
A sample CV that we like is here
Another sample CV with advice is here
Different companies will ask for different reference formats, but have your 3 references on standby for you to provide more information, as needed. You should get their agreement beforehand and have their full contact information.
Pick those that can speak to your work. If there is someone that knows the quality of your work, don't hesitate to ask them - providing a reference is a way that a very busy person can make a difference to someone starting out in her/his career.
Be aware of how people respond to reference requests.
- If someone says that they may not able to give you a good reference, including because they don't know you well enough, take this as information. It could be that they really are too busy, perhaps they don't know you enough to say anything positive, or perhaps they are not willing to give you a good reference.
- Writing a reference letter takes an hour, at least. Don't underestimate this - make it easier but highlighting what has to be written, by when, and bringing out the key points that you want highlighted.
Your two-year plan should be a regularly updated document where you lay out what you plan to achieve over the coming months. We recommend that you think even longer term, using the ideas discussed here
Consider each area of your life, as you cannot maximize your career without considering progress in other areas. Think of your career, your family/relationship, your health (physical and mental) and other areas of life that are important to you.
We suggest you write this down and share it with your mentors and peers for input and feedback. Update it and use it as a set of milestones to gauge progress.
Showcasing what you have done, by linking to your GitHub, is a high-value way to showcase your capbilities over a longer timeframe. This allows technical hiring managers to scan your code and understand what you are capable of.
No person is an island - having others that you can discuss approach with, share ideas, ideate on how to solve challenges, learn from and teach to, is valuable.
If you want to work as a Machine Learning Engineer or Data Engineer, you will need a good set of hardware to enable you to do your work efficiently and reliably. You will need to select and secure a machine that allows you to do this.
Knowledge of the cost of ensuring 24/7 internet access with 95% uptime. Electricity may be the limiting factor.
Developing internet access which is reliable, fast enough and fits with your work patterns (home vs. co-working space) is an essential piece of remote work. Depending on your country, you may be able to 'pay more for good internet' whereas in other countries, you may need to physically move to secure good internet. Electricity availability and where you choose to work from may play a role here too.
There is a reason why the famous FAANGs spend a lot of time, energy and focus on creating lovely places to work from, and to encourage their teams to work from there as much as possible - having others around in a helpful work environment can promote productivity.
- Case 1 - Fresh 10 Ac grad
- Case 2 - After 6 months of experience
- Case 3 - Deciding whether to go back to school or not