9 Key Takeaways From How To Become a Data Scientist by Adam Ross Nelson

After a successful book signing event for How to Become a Data Scientist at Open Data Science East in May, I wanted to check back in with ODSC folk by showcasing a short list of 9 important takeaways from the book.

Navigating your way into the field of data science, especially as an established professional, can feel akin to attempting one of the hardest tasks in the Triwizard Tournament — the formidable maze. Full of potential wrong turns and looming challenges, it’s a journey that can seem as intricate and confusing as the bewitched hedges of the Hogwarts maze.

In this realm, my book (hi, I’m Adam ross Nelson) — How to Become a Data Scientist emerges as your personal ‘Portkey’ — a magical object that has the power to transport its holder to a desired destination. This book, teeming with invaluable insights and practical guidance, acts as an enchanted aid that can instantly navigate you through the winding labyrinth toward your goal of becoming a proficient data scientist.

Much like the Triwizard champions relied on wands, brooms, or portkeys to overcome trials, mid- and late-career professionals stepping into or leveling up in the data science arena can trust How To Become a Data Scientist as their ‘Portkey.’ The purpose? To whisk them away from confusion and lead them toward clarity and success.

To preview this ‘Portkey,’ I am spelling out these eleven key takeaways from the book. If these takeaways resonate with you, I recommend that you equip you with the not-magic but magic-like tools you can find in the book. With this book’s guidance, you’ll discover you are more ready than you know. Remember, as in the magical world of Harry Potter, “Help will always be given at Hogwarts to those who ask for it.” In the same spirit, support will always be available in your data science journey to those who seek it.

Every wizard started as a mere Muggle, every data scientist began from a place of not knowing. Let’s traverse through the labyrinth of your data science journey together, with the portkey of knowledge at our disposal.

As we set out on this journey, let’s quickly chart the course for our magical exploration. We’ll first affirm the value of your experiences as an established professional and recognize that age is merely a number in this exciting realm of data science. We’ll then move onto the importance of domain knowledge and your readiness as an aspiring data scientist.

Next, we’ll debunk the myth of needing countless certifications to beat imposter syndrome, and instead focus on the importance of projects and portfolio entries. We’ll discuss the instrumental role of friends and family in your transition and how to modernize your resume to match the changing landscape.

Our magical ‘Portkey’ will also whisk us through the importance of social media and an updated online presence. Then, we’ll explore the strategic power of portfolios, and the evolving dynamics of recruiting. Last but not least, we’ll learn about the high return on investment for researching and negotiating your salary in the field of data science.

So grab tight onto your ‘Portkey,’ we’re ready to launch into the labyrinth of your data science journey, and I believe in you. Remember, in the world of data science, as in the magical universe of Harry Potter, “every great wizard in history has started out as nothing more than what we are now, students.” You are more ready than you may think. Let’s embark on this transformation together!

Data Science Isn’t Your First Passion

As an established professional, you’ve already wandered through the enchanting alleys of Diagon Alley, chosen your wand, and successfully navigated through numerous challenges in your professional life. Yes, data science might appear to be a different beast altogether, like facing a dragon in the Triwizard Tournament. But don’t forget, you have seen it all and then some.

You’ve battled with deadlines, charmed clients, brewed potent strategies, and created magical results in your respective fields. You’ve cast spells of innovation, levitated teams with your leadership, and conjured solutions out of thin air, similar to a master wizard conjuring a patronus in the face of adversity. You’ve pushed through struggles, conjuring resilience, and perseverance, much like a wizard facing a Boggart.

This isn’t your first rodeo. Data science likely isn’t your first professional challenge — and it might not even be your last. Remember, every trial you’ve faced, every success you’ve achieved, and every loss you’ve endured has seasoned you, forged you into a more proficient professional. Much like a wizard fine-tuning their spellcasting, you’ve honed your skills, becoming more effective, more insightful.

The magic of your previous professional experiences can’t be overstated. They are your magic wand in the field of data science. Your spells, your skills, the magical energy, the experiences — they all come together to form the foundation for your journey into data science.

This book, How to Become a Data Scientist, was written with you in mind. Your unique blend of experiences, your drive, your insights, and your magic. Let’s explore together how you can harness this magic and carve your niche in the realm of data science. Remember, the wand chooses the wizard, and the data science career chooses the professional who is more ready than they may think. So hold your wand high, let’s illuminate the path ahead together.

Data Science Is Not Just For The Young

Age, like the unforgiving confines of Azkaban, can seem like an unyielding barrier to those considering a pivot into data science. But let me assure you, age is just a number in this realm. Data science isn’t a game only for the young, like Quidditch. It’s an art form that is ageless and ever-evolving, much like the timeless magic that pervades the halls of Hogwarts.

It is never too late to embrace the spellbinding world of data science. Let’s take Guido Van Rossum as an inspiration. The first version of Python, a language now fundamental to data science, was published by Van Rossum when he was in his 30s. And his magic didn’t stop there; it only expanded, reaching millions of programmers and data scientists worldwide.

Consider this, the average age of professionals working in data science is over 41 years. Many enter or level up in data science in the middle or later portions of their careers. Your age does not define your ability to learn, adapt, and excel in this field. The world of data science is as welcoming to the experienced wizard as it is to a first-year student at Hogwarts.

Data science doesn’t discriminate by age; it embraces all who possess curiosity, the drive to learn, and the courage to venture into the unknown. So, whether you’re a first-year at Hogwarts or a seasoned wizard like Albus Dumbledore, there’s room for you in the realm of data science. Remember, you are more ready than you may think.

No need for a Time-Turner to change the past or predict the future, your time is now. With the wisdom of your years and the spark of your ambition, you can illuminate the path to success in data science. So, let’s move forward, armed with our ‘Portkey,’ navigating the labyrinth of data science, every step, a step closer to your new magical career.

Established Professionals Are Serious Data Science Contenders

Often, in the wizarding world, different strengths play to different games: Wizard Chess requires strategic wit, whereas Quidditch needs physical prowess and agility. Likewise, data science needs a blend of varied skills, and recruiters are on the constant hunt for this magical combination.

It’s challenging to find professionals who possess both domain knowledge and technical know-how. That’s where you, as an established professional, have a significant advantage. You’ve not only honed a wealth of business and industry knowledge but also gathered the wisdom that years of professional experience bring. You’ve developed strategic acumen, problem-solving abilities, and, most importantly, an understanding of your industry’s unique challenges and opportunities.

Recruiters value this combination. It enables you to comprehend the business’s intricacies and provide data-driven solutions that are practically viable. Your skills are as varied as the spells in a wizard’s repertoire. Each experience, each role, and each challenge you’ve faced in your career has been a spell learned, a skill acquired, and a strength developed.

Therefore, remember, you can become a data scientist not despite your age and experience but because of it. Your past professional experiences are like your own magical beasts, each one unique, each one powerful. They add depth to your understanding, making you a more attractive prospect for recruiters seeking seasoned wizards in the realm of data science.

Just as the elder wand responds to a true wizard’s command, the world of data science beckons established professionals like you, recognizing the power and potential that lies within your wealth of experience. Remember, you are more ready than you may think. And with this book as your guide, you will find your niche in data science, your elder wand in the professional world.

You Might Already Be a Data Scientist

In the wizarding world, the Invisibility Cloak is a magical artifact that provides its user with the power of becoming invisible. However, there’s a similar magic that often goes unnoticed in the professional world, particularly among established professionals transitioning to data science. This magic lies in your latent skills, abilities, and accomplishments.

Just as Harry Potter was initially oblivious to his magical heritage, many professionals are unaware of the data science skills they already possess. It’s not uncommon to intertwine our work with our identity, sometimes to our detriment. This is like believing the Invisibility Cloak to be an ordinary cloak, completely ignoring its extraordinary power.

I frequently encounter professionals who are already functioning as data scientists in their current roles. They analyze data, derive insights, and make data-driven decisions, all hallmark tasks of a data scientist. Yet, because they are trained for another role or because their job title doesn’t specifically state ‘data scientist,’ they underestimate their skills and are hesitant to identify as data scientists.

Don’t fall into this trap! Much like Harry Potter embracing his wizarding heritage, it’s crucial to recognize and embrace your data science abilities. Your technical know-how and business acumen, your knack for finding patterns and making informed decisions, are the spells you’ve been casting, maybe unknowingly, in your data science journey.

You may be more ready than you may think to step into or level up in data science, just like Harry was always a wizard, even before he knew it. This book is your Mirror of Erised, reflecting not just your deepest desires but also your hidden potential. Let’s pull back the Invisibility Cloak and reveal the data scientist you already are!

Imposter Syndrome and the False Patronus of Training

In the magical world of Harry Potter, Dementors represent despair and self-doubt, chilling the air around them and draining the joy out of life. In the professional world, the equivalent of Dementors is the insidious Imposter Syndrome. It instills doubt, diminishes accomplishments, and whispers in your ear, “you are not good enough.”

Imposter Syndrome often strikes when you’re transitioning into a new role or field, such as data science. The common antidote, or Patronus, if you will, that many seek is training. The belief is that by acquiring more knowledge, more certificates, more qualifications, they can drive away the shadowy Dementors of self-doubt.

But beware, this Patronus can be a false one! While continuous learning is indeed a cornerstone of success, using training as a cure for imposter syndrome can paradoxically make it worse. Why is that?

Imagine stepping into a room that keeps expanding every time you take a step forward. That’s what happens when you continually seek training to counteract your imposter feelings. The world of data science is vast and continuously evolving. The more you learn, the more you realize there’s so much more to know. Instead of driving away imposter syndrome, the cycle of endless training can feed it, making you feel even more like an imposter.

The cure for imposter syndrome isn’t more training. It’s recognizing your accomplishments, valuing your existing skills, and appreciating the unique perspective that your professional background brings to data science. Remember, you are more ready than you may think.

Instead of chasing the elusive Patronus of endless training, focus on acknowledging the magical skills you already possess. Use this book as your Marauder’s Map, helping you navigate through your journey, and remember, just like a wizard, you have the magic within you to ward off the Dementors of Imposter Syndrome.

Data Science Projects > Training

In the wizarding world, the Elder Wand is renowned as the most powerful wand. Its power is not a result of enchantments cast upon it, but the achievements of its successive owners. Similarly, in the world of data science, it’s not just about the training and certifications you hold, but the tangible achievements you can showcase — your data science projects.

Incorporating data science projects into your repertoire is akin to wielding the Elder Wand. It’s an assertion of your capabilities. A certificate may reveal what you have been taught, but a project showcases what you have accomplished, what you can do. It provides tangible evidence of your abilities to apply theoretical knowledge to real-world problems.

Just as the Elder Wand chooses the wizard, the project chooses the data scientist. It provides an opportunity for you to apply your knowledge, skills, and experience to a practical problem. The process of problem-solving, developing, and implementing solutions equips you with invaluable experience. It allows you to gain insights, learn from mistakes, and improve your skills — experiences that training alone cannot provide.

Hence, while certifications and trainings are important, they are not the end-all of data science competency. The balance of training and project work strengthens your professional image, providing solid evidence of your capabilities.

So, established professionals and aspirants in data science, machine learning, artificial intelligence, or advanced analytics, remember to value the power of projects. They’re your Elder Wand, your most reliable asset. You are more ready than you know. Like a wizard with an Elder Wand, with the right projects, you can cast a stronger, brighter Patronus against the Dementors of Imposter Syndrome.

Don’t Hide Your Data Science Transition From Friends + Family

Just as Harry Potter couldn’t have survived the Triwizard Tournament without his friends’ support, your transition into data science shouldn’t be a solitary journey. Invisibility cloaks may be handy in the wizarding world, but in the realm of career transition, it’s important to reveal your intentions.

Whether you’re a mid- or late-career professional contemplating or actively moving into data science, machine learning, artificial intelligence, or advanced analytics, you should share your plans with your friends and family. Like the members of Dumbledore’s Army supporting Harry, your loved ones can provide the emotional support, motivation, and even practical help you might need during this period.

Let’s not underestimate the power of connections. Friends, family, and colleagues from past careers may know someone who knows someone in data science. They can become your messengers, spreading the word about your professional evolution and potentially connecting you with opportunities.

Discuss your aspirations, the steps you’re taking, the challenges you’re facing, and the victories you’re achieving. This openness not only helps you get support and encouragement but also allows those close to you to understand your journey.

Remember, just like Harry needed Hermione and Ron, your transition into data science can be a smoother process with the help of your loved ones. You are more ready than you know, and with the support of those around you, you’re even readier than you think.

Adapting to the Changing Rules of the Job Search

Just as the magical Marauder’s Map revealed the changing passages of Hogwarts, today’s job search landscape is constantly shifting. The rules for creating an effective resume that worked 5, 10, or even 15 years ago may not hold the same power today, particularly when aiming for roles in data science, machine learning, artificial intelligence, or advanced analytics.

It’s crucial to adapt to the current dynamics and expectations of recruiters in these fields. Today, a one-size-fits-all resume doesn’t make the cut. A resume tailored to each specific role or company, emphasizing relevant skills, experiences, and projects, does.

Getting your resume right is crucial. In this highly competitive field, your resume is your first impression, and it could be your key to landing that interview. Therefore, hiring professional help with your resume isn’t an extravagance — it’s a smart investment, especially for mid- and late-career professionals transitioning into data science. Given the higher salaries associated with these roles, the return on investment can be substantial.

Just like Harry used the Marauder’s Map to navigate through the shifting corridors of Hogwarts, adapting to the changing rules of the job search can help you navigate through the job market’s labyrinth. Remember, you are more ready than you may think. Use your resources wisely and turn that ‘Mischief Managed’ into ‘Career Transition Managed.’

Powers of Salary Negotiation In Data Science

In the Wizarding World, even goblins recognize the importance of negotiation, as seen in Gringotts Bank. In the Muggle world, especially for those working in data science, machine learning, artificial intelligence, or advanced analytics, negotiation is just as crucial.

Many established professionals may feel apprehensive or uncertain about negotiating their salaries. However, it’s essential to remember that salary negotiation is not an adversarial confrontation, but rather a discussion of your value and worth. It’s an opportunity to align your compensation with your skills, experience, and the market rate.

Researching salary norms and expectations within your field pays off — literally. As my book, “How to Become a Data Scientist,” highlights, those who take the time to conduct salary research are over three times more likely to earn six-figure incomes.

The few hours you invest in researching and preparing for negotiation can translate into thousands, if not tens of thousands, more in your compensation package. This makes it a strategy with an incredibly high return on investment.

Just like the goblins of Gringotts would do, secure what you’re worth. Don’t shy away from the negotiation process. Remember, you are more ready than you know. Let’s transfigure that apprehension into confidence and secure the salary you deserve.

Conclusion

The adventure of stepping into or leveling up in data science, much like the world of Harry Potter, is filled with unexpected turns, new learning, and a profound sense of achievement. As we’ve journeyed through the key takeaways from “How to Become a Data Scientist,” I hope you’ve found the guidance as magical as a Portkey, capable of transporting you to your desired career destination.

Remember, established professionals like you have invaluable experience that can enrich your data science journey. It’s never too late to begin, and you may already be further along than you think. Tackling projects, keeping your support system informed, adapting to the current job search landscape, and being ready to negotiate salary are all part of the path forward. Each of these steps helps build a stronger, more polished online persona for you in the professional sphere.

The journey into data science can be as magical as a trip through Diagon Alley, filled with discovery and excitement. And just like every wizard began as a mere Muggle, every data scientist starts from a place of not knowing. If you’re feeling apprehensive, remember you are more ready than you think.

Embrace the journey, mid- and late-career professionals! Take this chance to evolve, to transform, to embark on a journey of continuous learning and growth. Your wand is already in your hand, your Portkey awaits. So, step forth with courage and confidence. After all, in the world of data science, just as in Harry Potter’s magical realm, everyone has to start someplace.

Thanks For Reading

Are you ready to learn more about careers in data science? I perform one-on-one career coaching and have a weekly email list that helps data professional job candidates. Visit coaching.adamrossnelson.com to learn more.

Thanks for reading. Send me your thoughts and ideas. You can write just to say hey. Twitter: @adamrossnelson LinkedIn: Adam Ross Nelson.

Originally posted on OpenDataScience.com

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