There is no skill that will earn greater dividends in your life than that of learning effectively.

The twin forces of Globalization and Technological Progress ensures that the days of a single career at one company are long past. The average person can be expected to change jobs 10 to 15 times, and planning for multiple careers in a lifetime is becoming a necessity.

Beyond career benefits, there’s also the personal ones. Have you ever tried to learn an instrument, before leaving it to gather dust in the attic? How about learning a language on Duolingo, only to never reopen…


Improve your sleep with seven actionable things you can start doing today

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An alarming statistic I came across recently is that 70% of Americans report insufficient sleep at least one night a month. These sleep deprived individuals then become hazards for others. For example, in a 2010 report American Automobile Association estimated that one out of every six (16.5%) deadly traffic accidents, and one out of eight (12.5%) crashes requiring hospitalization was due to drowsy driving.

The effects of sleep deprivation are also well known and include:


Learn how to get into self-tracking with minimal setup and maximum results

Datafloq

From steps, to sleep, to time spent online. Every day you’re generating data which has the power to inform and shape the way you live your life. For those willing to seek, lies a treasure trove of personal insights waiting to be discovered.

In this article we’ll cover:

1. Why you should start tracking your data today, in order to take advantage of compounding effects

2. What to track, and how to use this data to make better data-informed decisions

3. How to build robust tracking systems that will stand the test of time

I’ll also talk about my journey…


In this article, we’ll explore the differences between data scientists as Decision Support, Advisor and Integrated Partner

One of the best and worst parts of being a data scientist is the ambiguity that the role can often entail. Since data science is a relatively new function, the mandate and objectives aren’t always clear. This often means that the destiny of data science at a company lies in the hands of the data scientists, who often find themselves straddling both technical and non-technical domains. As such, being able to shape and define the role is key if you want to have a fulfilling career as a data scientist.

In this article, we’ll explore the progression that a data…


Transition seamlessly into remote work with these 7 habits

Transitioning to a remote work environment can be a jarring experience for some people. It’s not uncommon to see drastic drops in concentration and the quality of your work output to dwindle. Part of that can be things outside of your control, for example having kids in the house or chatty roommates. But leaving uncontrollable variables aside, there are still things that you can do to make the most out of working remotely.

In this article we’ll explore some of the habits of highly effective remote workers, giving you actionable habits that you can start doing today.

1. Create a Work Protocol

Setting a work…


Data scientists can use the Eisenhower Matrix to avoid simply taking orders, and instead, establish themselves as strategic advisers

Data scientists must constantly deal with the tension between short-term requests and long-term projects. Neglect the long-term projects, and you risk having minimal impact. However, neglect the short-term requests, and you may find yourself out of a job.

As a result, the best data scientists are those that can split their time effectively between short-term requests and long-term projects. In practice, this can be quite difficult because there is never a shortage of questions that your stakeholders may ask. Some of these questions are urgent and important, while others are neither important nor urgent.

Dwight Eisenhower, a former US President…


A framework for setting and achieving career goals

Setting goals, particularly around the end of December can be a great way to reflect and think about what you would like to get out of your career in the new year. In this article, we’ll discuss a framework for data scientists to use to achieve their career goals.

Since data science is an interdisciplinary field, the types of goals you set will be quite varied. A good way to partition the different types of goals is into the following three buckets: Technical, Behavioral and Professional.

For technical goals, you may want to improve your understanding of certain techniques or…


A 19th-century philosopher shares his thoughts on living

His work has influenced diverse groups including Marxists, Anarchists, and Conservatives. Freud, Heidegger, Jung, Hesse, Camus, Sartre, and Kafka have been influenced by his work in one form or another.

So who was Fredrich Nietzsche? Born in Germany in 1844, he was above all a keen observer of the human condition. Before making his mark on the world as a philosopher, he was a professor of philology at Basel University, a post he obtained at the young age of 24. …


Josh Pohlkamp-Hartt shares five tips he used to land his dream role at the Boston Bruins

The Boston Bruins are the fifth most valuable NHL franchise, valued at almost $1B by Forbes. With six Stanley cup victories, the team is able to produce over $200m in annual revenue.

Josh Pohlkamp-Hartt has been a hockey fan for as long as he can remember. Thus it didn’t take much to persuade him to leave his Statistician role at Apple to join the Boston Bruins as a data analyst. Before working at Apple for over 3 years, Josh completed his undergrad, Masters, and PhD at Queen’s University in Statistics.

In this article, Josh shares five tips he learned throughout…


Troy Shu shares his advice on starting a new role, becoming a better storyteller, stakeholder management, managing up, and building a consultancy

Troy Shu is currently a data scientist at Lyft, a transportation company with over 23 million users. He’s located in New York, where he’s helping build out the bikes and scooters side of the business. His work includes collaborating with data engineers to build data pipelines in Airflow, creating dashboards, conducting A/B tests, and working with product managers on product analytics.

Before Lyft, he worked as a data scientist at Squarespace, ran his own data science consultancy, worked as a software engineer at Bond Street as well as a research analyst at AQR (Where Wes McKinney created and open-sourced the…

Andrei Lyskov

 Data Scientist. I write about Data Science and other topics I find interesting

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