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Microsoft revamps developer interview process to better match real-world skills





Under the five-year reign of CEO Satya Nadella, Microsoft has made major strides in reforming its once-cutthroat corporate culture — an effort that’s even seeped into how it interviews software developers.

John Montgomery, partner director of program management at Microsoft, tells Business Insider that the core of cultural change is about making sure that teams are working with each other, all over the company, solving real problems for real customers. And so, Microsoft began rethinking its interview process to match that goal.

Traditionally, interviews at Microsoft and elsewhere can be highly technical — like, “reverse a linked list” — and include math games, like asking candidates to figure out how many ping pong balls would fill a 747. Both these types of questions really have little to do with what employees would actually do day-to-day at work — but even Google decided to discontinue its infamous brainteasers, because they didn’t actually test for anything worthwhile.

To that end, starting in early 2016, Microsoft’s developer division began rolling out the “Alternative Interview Framework,” which Montgomery detailed in a Medium blog post. It’s designed to better match an applicant’s skills to what the job really requires, says Montgomery, who spearheaded the effort as it spread through Microsoft’s developer division.

“We wanted it to be more like what people are expected to do at work,” Montgomery told Business Insider. “People are expected to collaborate. You can ask questions. We wanted it to be more like what you’re expected to do at work.”

The ‘Alternative Interview Framework’

Under the new process, Microsoft shares the interview questions in advance so that candidates can prepare. During the interview itself, a candidate might run through a real scenario or problem the team is trying to solve.

“When you walk a candidate through that process, every candidate brings something to each of those phases and each of those interviews,” Montgomery said. “Some candidates are great at a particular phase but not so great at others. It still makes them great hires. From that perspective of inclusion, it enables us to ask a broader array of questions.”

What’s more, rather than doing things one-on-one, a candidate talks to two interviewers at once— usually a senior employee and a junior employee. This gives the team two opinions on the candidate to consider, and it can actually make the candidate feel more comfortable as they get double the perspective on the team they’re trying to join.

Furthermore, the team uses blind feedback, meaning that all interviewers withhold their opinions on the candidate until the process is complete, at which time they all pool their opinions and come to a final decision. This can help reduce bias: It means that a second- or third-round interviewer won’t come into a meeting with the candidate with any preconceived notions from the first or second.

Redesigning the interview process

The team first tested the process on its own members over the summer of 2016, says Montgomery, interviewing each other to see if worked in practice as well as it does on paper.

“We haven’t had that much fun in a long time,” Montgomery said. “We also tested interview processes on people who are more senior. It’s a lot of fun when you’re effectively interviewing someone from your own team. We kept on learning and iterating to make it better.”

In so doing, says Montgomery, the team tried to apply the principles of product development to refining the new interview process. As they went, the team constantly reassess what was working and what wasn’t, iterating on the process on the fly.

In the last half of 2016, the team finally started running its first candidates through this brand new interview process, which has gradually expanded to more of the company since.

There’s still more Montgomery would like to improve on. Right now, the interview process is long, requiring candidates to take out an entire day. He thinks it would be useful to figure out if there ways to either shorten the process entirely, or at least spread it out over multiple days and gives candidates more time to reflect and think.

Also, he’d like to improve on making the scenarios more realistic and approachable for people who don’t have a background in professional software development, but may still be qualified candidates.

“We want to design an interview process centered around the interviewee,” Montgomery said. “It’s a manifestation of Microsoft culture and being more inclusive in identifying talent that a normal interview process might not identify.”

More empathy

Montgomery believes this new framework is more inclusive: By relying more on finding solutions to real problems, and less on esoteric or in-depth technical knowledge, it’s easier for people who didn’t come from traditional tech industry backgrounds to shine. Microsoft also works to make sure the interviewers reflect the company’s diverse workforce.

Montgomery points out that he himself took an unusual path to Microsoft. He majored in Russian literature, and then worked at trade press magazines and startups before joining Microsoft in 1998.

“I am introverted and I like to have time to reflect,” Montgomery said. “It turns out that that’s true for a lot of people. Everyone needs time to think. It has helped hugely for us to find people who are a little more thoughtful but good at what they do.”

Carol Smith, a senior program manager at Microsoft for the Open Source Programs Office, was one of the first candidates hired through the Alternative Interview Framework, and she says that interview process was the reason why she chose to work at Microsoft.

“The scenario-based interviewing process gave me an excellent sense of what my job at Microsoft and working with my coworkers would be like, much more so than any other interview process I’ve ever gone through,” Smith said. “It was the most difficult interview process I’ve ever gone through, and it was also the best.”

You can read Montgomery’s full blog post here.


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Trudeau Government Should Turn to Sustainable Floor Heating In Its New Deal





A consortium has been chosen by Public Services and Procurement Canada (PSPC) to manage the $1.1-billion overhaul of five heating and cooling plants in the National Capital Region. However, this decision has been met with a lot of disapproval by the country’s largest federal public service union.

Early June, the department announced that Innovate Energy has been awarded the 30-year contract “to design, retrofit, maintain and operate the plants,”winning the bid over a rival group that included SNC-Lavalin.

Minister of Environment, Catherine McKenna, said the federal government was “leading by example” in its bid to drastically reduce the amount of greenhouse gas emissions across the country. McKenna noted that by supporting this project, they’re utilizing heating and cooling infrastructure to promote a more environmentally friendly option.

“We’re very proud that our government is working with partners like Innovate Energy to modernize this critical infrastructure,” she said during the announcement at one of the facilities that will be upgraded, the Cliff Heating and Cooling Plant in downtown Ottawa.

The plants would be known as the district energy system and would heat 80 buildings in the area with steam. It is also expected to cool 67 of these buildings with chilled water through more than 14 kilometres of underground pipes.

Under the Energy Services Acquisition Program, PSPC will be tasked with modernizing the outdated technology in the plants to lower emissions and supportgrowth in the eco-friendly technology sector.

During the first stage of the overhaul, the system would be converted from steam to low temperature hot water and then switched from steam to electric chillers—with the estimated completion date being 2025. PSPC notes that the project will reduce current emissions by 63 per cent, the equivalent of removing 14,000 non-eco-friendly cars off the road.

Afterwards, the natural gas powering the plant will then be replaced by carbon-neutral fuel sources, which according to estimated will reduce emissions by a further 28 per cent. The renovation project is bound to save the government an estimated fee of more than $750 million in heating and cooling costs in the next 40 years.

Furthermore, the implementation of radiant floor heating in Ottawa by the federal government would be an additional step in driving its agenda for a more eco-friendly state.

According to the U.S. Department of Energy’s Energy Savers website, radiant floor heating has a lot of benefits and advantages over alternate heat systems and can cut heating costs by 25 to 50 per cent.

“It is more efficient than baseboard heating and usually more efficient than forced-air heating because no energy is lost through ducts,” the website states.

Radiant floor heating provides an equal amount of heat throughout a building, including areas that are difficult to heat, such as rooms with vaulted ceilings, garages or bathrooms. Consideringit warms people and objects directly—controlling the direct heat loss of the occupant—radiant floor heating provides comfort at lower thermostat settings.

“Radiators and other forms of ‘point’ heating circulate heat inefficiently and hence need to run for longer periods to obtain comfort levels,” reports the Residential Energy Services Network (RESNet).

Radiant heating is a clean and healthy option—a perfect choice for those with severe allergies—as it doesn’t rely on circulating air, meaning there are no potentially irritating particles blowing around the room. Additionally, it is more energy efficient, aesthetically pleasing with wall radiators or floor registers and virtually noiseless when in operation.

“They draw cold air across the floor and send warm air up to the ceiling, where it then falls, heating the room from the top down, creating drafts and circulating dust and allergens.”

It is important for the leadership in Ottawa to equally drive the adoption of radiant floor heating as doing this would lead to increased usage in residential buildings—and even government-owned buildings.

However, in October, the Public Service Alliance of Canada (PSAC), a representative body of employees of the plants,began a campaign target at the government against their decision to use a public-private partnership (P3) for the retrofitting project, citing concerns about costs and safety.

According to the union, outside employees won’t be bound to the same health and safety standards of government workers and that typically P3 projects cost a lot more than traditional public financing deals.

The union demands that the government scraps the proposed project and meet PSAC members and experts to brainstorm on a new way forward that would ensure federal employees continue to operate and maintain the plants.

However, parliamentary secretary to public services and procurement minister, Steve MacKinnon said that the union officials have consulted him but that after conducting an analysis, the P3 option was still the best for the job.

“We didn’t have (to) sacrifice on safety or health — we didn’t have to sacrifice on job security,” he said.

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Steps to becoming a Data Scientist





Data science has become one of the most in-demand career paths in this century, according to Business Insider. With the amount of information being circulated online, it has created a huge demand for storing, interpreting and implementing big data for different purposes—hence the need for a data scientist.

Today, there too much information flying around for regular people to process efficiently and use. Therefore, it has become the responsibility of data scientists to collect, organize and analyze this data. Doing this helps various people, organizations, enterprise businesses and governments to manage, store and interpret this data for different purposes.

Though data scientists come from different educational backgrounds, a majority of them need to have a technical educational background. To pursue a career in data science, computer-related majors, graduations and post graduations in maths and statistics are quite useful.

Therefore, the steps to becoming a data scientist are quite straightforward.  After obtaining a bachelor’s degree in an IT related field—such as computer science, maths or physics—you can also further your education by obtaining a master’s degree in a data science or any other related field of study. With the necessary educational background, you can now search for a job and obtain the required experience in whichever filed you choose to invest your acquired skills.

Here are the necessary steps to be taken to become a data scientist.

Step 1: Obtain the necessary educational requirements

As earlier noted, different educational paths can still lead to a career in data science. However, it is impossible to begin a career in data science without obtaining a collegiate degree—as a four-year bachelor’s degree is really important. However, according to a report by Business Insider, over 73% of data scientist in existence today have a graduate degree and about 38% of them hold a Ph.D. Therefore, to rise above the crowd and get a high-end position in the field of data science, it is important to have a Master’s degree or a Ph.D.—and with various online data science masters program, obtaining one is quite easy.

Some institutions provide data science programs with courses that will equip students to analyze complex sets of data. These courses also involve a host of technical information about computers, statistics, data analysis techniques and many more. Completing these programs equips you with the necessary skills to function adequately as a data scientist.

Additionally, there are some technical—and computer-based degrees—that can aid you begin a career in data science. Some of them include studies in, Computer Science, Statistics, Social Science, Physics, Economics, Mathematics and Applied Math. These degrees will imbibe some important skills related to data science in you—namely, coding, experimenting, managing large amounts of data, solving quantitative problems and many others.

Step 2: Choose an area of specialization

There rarely exists an organization, agency or business today that doesn’t require the expertise of a data scientist. Hence, it is important that after acquiring the necessary education to start a career as a data scientist, you need to choose an area of specialization in the field you wish to work in.

Some of the specializations that exist in data science today include automotive, marketing, business, defence, sales, negotiation, insurance and many others.

Step 3: Kick start your career as a data scientist

After acquiring the necessary skills to become a data scientist, it is important to get a job in the filed and company of your choice where you can acquire some experience.

Many organizations offer valuable training to their data scientists and these pieces of training are typically centred around the specific internal systems and programs of an organization. Partaking in this training allows you learn some high-level analytical skills that were not taught during your various school programs—especially since data science is a constantly evolving field.

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Artificial intelligence pioneers win tech’s ‘Nobel Prize’





Computers have become so smart during the past 20 years that people don’t think twice about chatting with digital assistants like Alexa and Siri or seeing their friends automatically tagged in Facebook pictures.

But making those quantum leaps from science fiction to reality required hard work from computer scientists like Yoshua Bengio, Geoffrey Hinton and Yann LeCun. The trio tapped into their own brainpower to make it possible for machines to learn like humans, a breakthrough now commonly known as “artificial intelligence,” or AI.

Their insights and persistence were rewarded Wednesday with the Turing Award, an honor that has become known as technology industry’s version of the Nobel Prize. It comes with a $1 million prize funded by Google, a company where AI has become part of its DNA.

The award marks the latest recognition of the instrumental role that artificial intelligence will likely play in redefining the relationship between humanity and technology in the decades ahead.

Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society,” said Cherri Pancake, president of the Association for Computing Machinery, the group behind the Turing Award.

Although they have known each other for than 30 years, Bengio, Hinton and LeCun have mostly worked separately on technology known as neural networks. These are the electronic engines that power tasks such as facial and speech recognition, areas where computers have made enormous strides over the past decade. Such neural networks also are a critical component of robotic systems that are automating a wide range of other human activity, including driving.

Their belief in the power of neural networks was once mocked by their peers, Hinton said. No more. He now works at Google as a vice president and senior fellow while LeCun is chief AI scientist at Facebook. Bengio remains immersed in academia as a University of Montreal professor in addition to serving as scientific director at the Artificial Intelligence Institute in Quebec.

“For a long time, people thought what the three of us were doing was nonsense,” Hinton said in an interview with The Associated Press. “They thought we were very misguided and what we were doing was a very surprising thing for apparently intelligent people to waste their time on. My message to young researchers is, don’t be put off if everyone tells you what are doing is silly.” Now, some people are worried that the results of the researchers’ efforts might spiral out of control.

While the AI revolution is raising hopes that computers will make most people’s lives more convenient and enjoyable, it’s also stoking fears that humanity eventually will be living at the mercy of machines.

Bengio, Hinton and LeCun share some of those concerns especially the doomsday scenarios that envision AI technology developed into weapons systems that wipe out humanity.

But they are far more optimistic about the other prospects of AI empowering computers to deliver more accurate warnings about floods and earthquakes, for instance, or detecting health risks, such as cancer and heart attacks, far earlier than human doctors.

“One thing is very clear, the techniques that we developed can be used for an enormous amount of good affecting hundreds of millions of people,” Hinton said.

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