Lesson 3 — Cultivating Trust

Making a meaningful impact hinges on effectively communicating your ideas to those who can bring them to fruition. This typically includes product managers (who define the product vision and strategy), designers (who create the product), and engineers (who assess the technical viability of the concept and execute it). The insights you contribute and the recommendations you put forth will steer the team's efforts.

It’s vital to master the art of persuasion to ensure that your ideas are acknowledged and valued. (For a deeper dive, check out my comprehensive post ⬇️ on transforming insights into actionable outcomes.)

Now, onto lesson #3! While it may seem self-evident, trustworthiness is fundamental to the data scientist's role and is a trait that develops over time. You might be wondering, "But how can I gain that trust as a newcomer?"

Rest assured, a company hires you because they have faith in your reliability. Therefore, the foundation of trust is already in place, and your job is to reinforce it. So, how can you lay the groundwork for trust as a newcomer?

We’ve already discussed how sharing your work and soliciting feedback can enhance your credibility, but let’s explore additional strategies:

1. Be Proactive and Inquisitive

   One natural gift I possess is an insatiable curiosity that often leads me to ask numerous questions. While this might not have served me well in high school, the professional realm—especially in tech—operates under different guidelines. Colleagues frequently commend my ability to dissect a topic through inquiry.

Demonstrating a genuine interest in understanding the nuances of a subject will position you as a reliable source of knowledge and decision-making.

2. Embrace Humility

   It’s important to acknowledge when you don’t have all the answers. Being humble about your uncertainties is critical. If you lack knowledge in a specific area, it’s best not to pretend otherwise, as this can hinder your progress.

Transparency regarding your confidence in your results is essential in a field where certainty is rare. Communicating your ongoing efforts to find solutions is the first step toward growth. Others will appreciate your honesty, and it will enhance your reliability.

Solutions can be elusive, but as data scientists, we thrive on unearthing hidden insights. It’s through this process that you’ll grow and learn from others.

Lesson 4 — Seek Guidance from Experts

Imagine this scenario: I'm engaged in a causal inference project—a complex area of statistics aimed at discerning causal relationships based on observational data. Although I had studied this topic in college, my memory was hazy.

While researching, I sought advice from peers and revisited past projects for inspiration. After considerable effort, I finally decided to reach out to experienced data scientists for clarity on a particular concept. To my surprise, a causal inference expert pointed out that I was fundamentally misguided, leading me to realize my entire methodology was flawed.

This situation taught me a valuable lesson: While it's crucial to develop independent problem-solving skills, knowing when to ask for help is equally important. The benefits of seeking guidance from the right people are numerous:

1. Expert Insights

   Gaining insights from seasoned professionals can enhance both your project and your skills. Remember, you may be a newcomer, but you're surrounded by experts; don’t hesitate to seek their advice.

To do this effectively, look for previous projects that align with your current work and reach out to those who were involved. They’ll likely offer valuable insights and help you identify any inconsistencies.

2. Avoiding Mistakes

   Asking for help can save you from the frustration of realizing you've veered off course. This not only alleviates stress but also ensures you stay on track with your timeline.

Just remember to put in a solid effort before seeking assistance. If you find yourself stuck longer than expected, it's time to ask for help.

Final Thoughts — Be Kind to Yourself

If you’ve made it this far, you deserve a huge round of applause! Thank you for sticking with me.

As I conclude, here’s my most important takeaway: No one expects you to be a master from day one or even after a hundred days, especially in tech! Working alongside more experienced colleagues presents a unique opportunity for growth. However, it took time for me to accept that being the least experienced person in the room was okay.

I used to compare myself with my peers, often feeling overwhelmed by how quickly they could deliver results or juggle multiple projects.

It's essential to recognize that perfection is not the expectation when you're just starting out. You're a newcomer, and no one anticipates you to match the skills of seasoned professionals immediately. But remember, you're part of a team, and they will support you. Eventually, you'll find your voice and confidence—it's just a matter of time and dedication.

Striving for excellence is important, but it’s equally crucial to be gentle with yourself. Instead of trying to emulate your seniors, focus on asking questions organically and being authentic. Connecting with fellow newcomers can also provide perspective and reassurance that you're not alone in your journey.

So, my final piece of advice: give yourself grace and stop the unnecessary self-criticism. If this doesn’t resonate with you, that's fine too, but it’s always worth remembering to be kind to yourself.

Your feedback is invaluable!

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The first video titled "Lessons Learned From the NFL and Spotify on Data Discovery" explores valuable insights on data discovery strategies that can enhance your data science skills.

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