Plaid is a company that offers top-class financial tools millions of people rely on to achieve healthier financial goals. With partnerships with thousands of Fortune 500 businesses, and a host of large banks, Plaid simplifies the process of connecting financial accounts to the apps and services users desire. 

As a Plaid Software Engineer, you will have the opportunity to develop expertise in fintech by working closely across functions. You will be responsible for driving impactful initiatives across the organisation, taking ownership of features from ideation to production, and developing performant systems. You will tackle complex problems in backend systems, API integrations, distributed systems, and large-scale system architecture. 

The estimated total pay for the Plaid Software Engineer role is $200,951.

The Plaid software engineer interview process consists of three rounds, each of which is designed to assess your technical and behavioural competencies:

Prepare for success in the Plaid software engineer interview process. Learn about the interview stages, coding challenges, system design questions, and expert tips to help you land your dream job at Plaid.

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Cracking the Plaid Software Engineer Interview: Tips and Insights

Detailed, specific guidance on the Plaid Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage.

Flexport is a major platform that facilitates global trade in an industry that constitutes 12% of the world's GDP. To fulfill its mission of improving the user experience in global trade, the company actively recruits extremely high-quality and well-paid software developers.

Flexport is considered a highly sought-after employer in the tech industry. As an SWE (Software Engineer) at Flexport, you will work on products that are literally reshaping the logistics and supply chain industries.

In terms of compensation, Flexport offers competitive salaries, equity packages, and a comprehensive benefits package, which includes health insurance, retirement plans, and other perks. The average salary for software engineers at Flexiport ranges between US$207.58K to US$480.83K per annum:

Software Engineer I (Entry Level): US$207.58K

The Flexiport software engineer interview process is pretty comprehensive and includes the following 5 rounds:

Discover the comprehensive interview process for software engineers at Flexport. Learn about technical assessments, coding challenges, behavioral interviews, and tips to excel in the hiring process.

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Flexport Software Engineer Interview Process: A Guide to Success

Detailed, specific guidance on the Flexport Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage.

Flexport Software Engineer Interview Guide

Datadog is actively expanding its team and filling a variety of tech roles, with Product Management being one of the most exciting opportunities available to talented tech individuals.

Product Managers at Datadog work on cutting-edge technologies as part of a dynamic team that's shaping the future of IT infrastructure monitoring and management. They play a crucial role in driving the product roadmap, working closely with a talented team of engineers and marketers to innovate and deliver cutting-edge technologies.

With an average salary of US$215K /year going up to US$485,000 /year based on seniority levels, the product manager role at Datadog is highly competitive and sought-after. For passionate product aspirants who are eager to take on new challenges, you can expect a hyper-growth, dynamic environment to elevate your career and make a meaningful impact in the tech industry.

Datadog's interview process primarily consists of 4 main rounds and the difficulty level of the interview questions is medium. Candidates have described the PM Datadog interview to be rigorous and long, spanning 1 to 2 months, however, their experience has been generally positive.

The interview rounds for a product manager at Datadog are pretty standard. You'll have 

Get insider tips and insights into the Datadog product manager interview process. Learn about the key stages, common interview questions, and strategies to succeed in landing a product management role at Datadog.

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Cracking the Datadog Product Manager Interview: Tips and Insights

Detailed, specific guidance on the Datadog Product Manager interview process - with a breakdown of different stages and interview questions asked at each stage.

Fiverr is looking for top talent that can oversee software development from design to production while working with cutting-edge technologies. The company offers a fast-paced, dynamic environment for passionate software engineers to contribute meaningful to technological innovations and progress in their careers.

The average salary of a Software Engineer at Fiverr is US$163.07K per annum, including base potential stocks and bonuses. It can go up to a yearly total compensation of $229,087 depending on the seniority of the position and location of the job.

Based on what's reported by candidates on Levels FYI,

A L3 Distributed Systems Back-End Engineer earns an average US$120,000 per annum.

As a Full Stack Engineer at Fiverr, you can earn an average of US$169,000 per annum.

The interview process at Fiverr for a software engineering role is comprehensive, slightly tough, but fair. It typically begins with a phone interview, and is followed by 3 technical interviews—first with a team lead, then a group manager, and finally VPs. The process from applying with a resume to receiving an offer letter can take 2 weeks or more.

Discover the key aspects of the Fiverr software engineer interview process and gain valuable tips to succeed. Explore the technical challenges, behavioral questions, and coding assessments that form the foundation of the hiring process.

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Mastering the Fiverr Software Engineer Interview Process: Tips and Insights

Detailed, specific guidance on the Fiverr Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage.

A PM at DoorDash is responsible for owning end to end product strategy, delivery, and impact for a component or product within the DoorDash ecosystem. You'd own a key aspect of the ecosystem which directly ties back into a key metric for the company; and it could be across any part of the 3-way marketplace (dashers/riders, restaurants and bookers). 

From a day-to-day point of view - Product at DoorDash will involve staying on top of the market landscape (i.e. keeping track of both macro trends and competition); identifying customer needs; building out a product vision & strategy - and then executing on it, all the way from working with UX for designing a great customer experience, with Engineering for high performance and reliability, to Data for extracting insight from experimentation and identifying iterations.

DoorDash interviews can get pretty challenging -the company pays well - but also aggressively filters out candidates who miss a trick. Broadly speaking, you'd have to index well on being able to strategize and think big while solving real customer problems (tested via Product Sense interviews), execute reliably and pragmatically (tested via Product Prioritization and Product Analytics), and being a good "working fit" for DoorDash' culture (tested via "Values" interviews).

This guide is going to deepdive through the process and provide recent interview questions for you to mull over when you're preparing for the interview. When you're ready you can also book mock interviews with DoorDash PM coaches to "sense check" your readiness level.

The interview process is divided into several stages:

Take home assessments - occurring at decreasing frequency; roughly 25% of all candidates reporting a take-home in the last 12 months.

Phone screen with hiring manager and/or current PM

(Virtual) On-site interviews - 3-4 rounds covering Product Sense, Product Analytics, Product Prioritization and Values

Detailed overview and guidance re: the DoorDash PM, Sr. PM and Group PM interview process. Curated with the help of recent candidates; updated monthly; and reviewed by DoorDash PM coaches.

DoorDash Product Manager (+ SPM & GPM): Interview Deepdive in 2023

Coinbase is actively seeking individuals with a keen product-focused mindset, who possess the ability to bring about transformative innovations in the crypto domain, impacting billions of users. By joining their Crypto team as a Product Manager, you will have the opportunity to play a pivotal role in revolutionizing the financial industry, while simultaneously positioning yourself as a leading thinker and innovator in the crypto space. 

The remuneration for product managers at Coinbase ranges from US$ 190.5K for Associate Product Managers to US$ 500.7K for Senior Product Managers, and is typically commensurate with the candidate's level of experience and location of the job. While previous experience in product management, entrepreneurship, or early stage engineering is preferred, it is not a prerequisite for the role.

To maximize your chances of success, we will provide you with insights into the company's interview process, including the types of questions that are typically asked, and offer key preparation tips.

At Coinbase, the competition for PM interviews is intense. The team evaluates candidates based on several crucial traits. These include the capacity to comprehend and convey complex issues, well-organized thinking, and the ability to generate innovative solutions on the spot. In addition, a profound comprehension of technical challenges and trade-offs is highly valued. Candidates should also possess self-awareness, a positive attitude, and the ability to communicate concisely and effectively.

You'll face challenging questions across the different stages of the interview which include

A phone screen with your hiring manager, and

The on-site interview (currently virtual).

Discover the Coinbase product manager interview process and gain valuable insights and tips to help you navigate the selection process successfully. Learn about key interview stages, expected skills, and strategies for showcasing your expertise.

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Coinbase Product Manager Interview Process: Insights and Tips

Detailed, specific guidance on the Coinbase Product Manager interview process - with a breakdown of different stages and interview questions asked at each stage.

Joining the software engineering team at Patreon provides an exciting opportunity for candidates to work on innovative projects and make a significant impact in the company's continued growth and success. Since the company is undergoing significant growth, it is actively expanding their team to develop Patreon v2.0 with enhanced native features. 

Thus, Patreon is currently seeking top-notch engineers and has been aggressively recruiting top talent, as evidenced by the recent addition of several senior-level employees from major tech companies like Meta, Twitter, Instagram, Amazon, and Tesla. 

The average yearly total compensation of Patreon Software Engineers ranges between $257K - $341K, depending on the job location and seniority level.

There are four main stages to the Patreon Software Engineer role:

Discover what it takes to excel in the Patreon software engineer interview process. Get insights into the technical challenges, coding assessments, and cultural fit evaluations. Prepare yourself for success!

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Inside the Patreon Software Engineer Interview Process: A Comprehensive Guide

Detailed, specific guidance on the Patreon Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage.

Patreon Software Engineer Interview Guide

Adobe hires Product Marketing Managers (PMMs) throughout the year; it is a reputed, large-scale software company with a range of products and services that require PMMs to support them. 

Product marketing managers are highly sought-after in the technology industry and in-demand at companies like Adobe. They ensure that products are properly positioned, differentiated from competitors, and launched successfully. 

Since Adobe launches innovative software solutions regularly and thus, offers the opportunity to work with cutting-edge technology, working as a PMM at the company is a highly lucrative role for talented professionals looking to be part of a team that is shaping the future of technology. Not to members, Adobe offers competitive salaries and benefits, the estimated total pay for a Product Marketing Manager at Adobe is $226,668 per year.

In this article, we'll discuss what the interview process for a PMM candidate at Adobe might look like. So, let's dive right in.

The Adobe Product Marketing Manager Interview process takes around two months from applying to receiving a job offer. It is a rigorous process, consisting of multiple rounds of interviews, some with leaders and others with teams or groups that you would be working with closely in the role. These rounds are designed to cover a wide range of areas, from technical and analytical skills to IQ and ingenuity.

The Interview consists of three primary rounds, each focusing on different aspects of the candidate's qualifications and experience

Round 1: Introductory Phone Call with Adobe's Talent team

Round 2: Hiring Manager Interview (30 minutes)

Round 3: Face-to-Face Interviews (with a panel of up to 4 PMM/PMM stakeholders)

Discover what to expect during the Adobe product manager interview process. Learn about the interview stages, common questions, and valuable tips to help you prepare and excel in your pursuit of a product management role at Adobe.

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Inside the Adobe Product Manager Interview Process: Tips and Insights

Detailed, specific guidance on the Adobe Product Marketing Manager interview process - with a breakdown of different stages and interview questions asked at each stage.

Adobe Product Marketing Manager Interview Guide

Apple is a technology conglomerate that designs, manufactures, and sells consumer electronic goods, software/apps, and a variety of online services. Given the massive amounts of data its platforms such as Siri, iCloud and other online services constantly generate and handle, Apple needs data scientists who can help its platforms make sense of these huge data.

The role of a data scientist at Apple is different from those at other companies. It differs because Apple needs what is called full-stack data scientists. Apple expects its data scientists to be dynamic enough to work in different roles across its various teams such as the machine learning/AI-centric Siri team, analytics-heavy iTunes team, marketing, and sales teams, etc.

Practical experience with and theoretical understanding of various machine learning algorithms

Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark

Mathematics, computing, and statistical skills

Coding skills in a general programming language such as Python, Scala, or Java

Ability to extract meaningful business insights from data and a knack for identifying patterns.

Excellent communication and presentation skills

The Apple interview process is similar to that of other major tech companies such as Facebook, Google, and Amazon. Candidates are required to submit their applications online. Those who make it to the interview round receive a call from the recruiter, usually an HR manager for the company. After that, candidates face a technical phone screen. Those who make it beyond this screening stage are called for an elaborate onsite interview. The location for the onsite interview may vary according to roles. It may either be in Cupertino, Austin or some other Apple campus.

Prepare for your Apple Data Scientist interview with our comprehensive interview guide. Get insights, tips, and sample questions to ace your interview at Apple.

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Apple Data Scientist Interview Guide | Prepfully

Lyft is a tech company that is rapidly expanding its engineering team and looking for exceptional software engineers. 

Working at Lyft as a software engineer means having the opportunity to work on highly technical and complex systems that have a significant impact on millions of users worldwide. The engineers at Lyft are part of a dynamic and innovative team that is always looking for ways to improve the user experience. They work closely with cross-functional teams, including engineering, product, data science, analytics, and operations, to develop programs that enhance the user experience for passengers and drivers.

As the company continues to grow, software engineers can look forward to ample opportunities to take on exciting new challenges and play a crucial role in the company's success.

The average Lyft software engineer salary ranges between US$220.9K for an entry-level SWE to US$541.17K for a staff engineer.

Lyft interviews consists of the following four stages

Discover what to expect in the Lyft software engineer interview process. Get valuable tips, insights, and guidance to help you prepare and succeed in landing a software engineering role at Lyft.

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Inside the Lyft Software Engineer Interview Process: Tips and Insights

Detailed, specific guidance on the Lyft Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage.

A Data Scientist at Pinterest is responsible for collecting, analyzing, and interpreting large amounts of data to gain insights and inform business decisions. The data collected and analyzed can range from user behavior and engagement data to financial and marketing data.

A Data Scientist at Pinterest works closely with other teams such as product, engineering, and marketing to understand their needs and provide data-driven solutions to complex problems. They also work on developing predictive models and algorithms to help the company make informed decisions about product development, marketing campaigns, and resource allocation.

Pinterest hires Data Scientists across the company and there are different seniority levels depending on the scope and expected impact. They have Senior, Principal, Director and Manager level roles. They also have openings for ML engineers and Applied Research Scientists.  For instance, there was recently a role in Ads Quality team as a ML Engineer - the goal being to develop and execute a vision for the evolution of the machine learning technology stack within Ads Ranking. You will work on tackling new challenges in machine learning and deep learning to advance the statistical models that power the ads engagement and delivery that bring together Pinners (i.e. what Pinterest calls its employees) and partners in this unique marketplace. 

It is worth noting that the available positions and locations can change frequently, so it is recommended to regularly check the career page for the latest updates.

How to Apply for a Data Scientist Job at Pinterest?

To apply for a Data Scientist job at Pinterest, you will need to visit the Pinterest's career website and search for open Data Scientist positions. Once you have found a position that you are interested in, you will be able to submit an application online. However, we would highly recommend taking the referral route if you know someone in the company as it increases your chances meaningfully. One tip regarding your resume - make a few tweaks for the position and the role you are applying for which will help you have a better chance compared to other candidates. For instance, some DS roles might explicitly call for a background in ML; others might need you to be very good at visualization - these are exactly the sort of things you should then highlight if you have past experience doing. If you're not sure how to do that, Prepfully offers a resume review service, where actual recruiters will give you feedback on your resume.

As a part of the Pinterest Data Scientist interview, the candidate will need to go through multiple interview rounds:

1.  Phone Screening - The phone screening will be a conversation with a recruiter, detailing your technical background, your past relevant projects, and a quick assessment of your skill sets based on your resume.

2. Technical Interview - The second primary round of an interview process at Pinterest involves a technical interview with a senior data scientist. This interview is designed to assess your technical skills and knowledge in the field of data science.

3. Onsite Interview Rounds - The final onsite primary round of an interview process at Pinterest is an extensive evaluation of your technical and professional skills. This onsite interview consists of multiple rounds designed to assess different aspects of your expertise and capabilities. 

Make sure you look at all the interview questions and tips in our Pinterest Data Scientist Interview Guide

Data science is a crucial part of Shopify’s mission to make commerce better for everyone. Data science at Shopify principally includes two types of work: building products directly backed by data (e.g. machine learning models), and listening to their voice to figure out what to build and how to build it. 

Shopify looks more for Data Scientists who have solved challenging problems than those familiar with specific tools or technologies. They are looking for talented data scientists to help them better understand their merchants and buyers.

Shopify hires Data Scientists across the company and there are different seniority levels depending on the scope and expected impact.They have Senior and Staff level roles and some openings for Data Science Managers. For instance, there was recently a role in Merchant Services - the goal being to give small businesses targeted advice that can help them better compete with larger ecommerce players. Given the scope and complexity of this undertaking, this was a Staff level role.

As a Data Scientist, you are expected to play a crucial role pushing forward product development across multiple domains. Data Scientists do this by informing high-level product strategy and execution, building a strong and broad operating picture allowing Shopify to move quickly, and/or improving underlying algorithms, heuristics and rules powering individual products - making the Shopify Data Scientist a sought-after role!

How to Apply for a Data Scientist Job at Shopify?

Take a look at Shopify’s website and visit their careers page. You'll find plenty of opportunities along with the Data Scientist role at Shopify, and you can easily apply to roles directly on the site. However, we highly recommend taking the referral route if you know someone in the company as it significantly increases your chances. Before you hit the apply button, make sure you read the job requirements thoroughly. Nothing's more frustrating than getting caught off guard during an interview. If you want to increase your chances even more, tailor your resume to align it with the qualifications and experiences listed in the job posting. It'll make you stand out from the rest. If you're not sure how to do that, Prepfully offers a resume review service, where actual recruiters will give you feedback on your resume.

Responsibilities of a Data Scientist at Shopify

The responsibilities of a data scientist at Shopify across roles can broadly be seen as-

Actively seeking out and promoting projects that tackle vital issues.

Utilizing Data Engineering frameworks (such as Starscream and Seamster) to gain insights.

Being sufficiently familiar with BI tools such as Mode, PowerBI, and Tableau - to be able to visualize data in an effective way to drive insights.

Collaborating with teams such as product, engineering, and other business leaders to make data-driven decisions.

Utilizing analytical tools to identify opportunities and guide execution.

Developing actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products.

Influencing leadership to drive more data-informed decisions across the organization.

Skills and Qualifications needed for Data Scientists at Shopify

Here are some skills and qualifications that will help you excel in your Data Science interviews at Shopify.

It's beneficial to have at least 5+ years of experience in Data Science roles, which can help you stand out from other candidates. From what we’ve seen - candidates with less than 5 years of experience often struggle - even to get interview calls; let alone the interview loop.

Brush up on your SQL skills and make sure you have a solid understanding of software engineering fundamentals.

Being proficient in Object Oriented Programming will give you an edge in the interview process. This is because Data Scientists at Shopify are expected to be pretty much “full stack” in nature.

Showcase your experience with applied statistics and your ability to solve quantitative problems.

Be prepared to explain how you've turned analytical insights into clear recommendations, and demonstrate your ability to communicate effectively with technical and non-technical stakeholders.

Highlight your understanding of dimensional modeling and the ability to scale ETL pipelines.

Having experience launching productionized machine learning models at scale will give you an edge over the other candidates.

A Domain experience in e-commerce, marketing or SaaS can help to tailor your approach in a specific industry.

As a part of the Shopify Data Scientist interview, the candidate will need to go through multiple interview rounds:

1. Recruiter call or Behavioural Round - The first round is to have a quick discussion about your work experiences and the roles you’ve had in the past company.

2. Pair Programming or Coding round - The second round is to test your data science concepts and SQL and Python-related concepts. This is to test your analytical skills and to see the approach you take to solve the given problem.

3. The final round of Shopify Data Scientist interviews will usually be a combination of technical rounds and behavioral rounds. You will have a panel of interviewers (often senior data scientists) who will assess you across a range of skills and experiences. The skills you will be likely tested on are: product analytics, metric analysis and behavioral/leadership skills.

Get expert tips and insights to prepare for a data scientist interview at Shopify. Our comprehensive guide covers common interview questions, technical skills, and non-technical skills that can help you succeed in the interview process. 