Applying for a data scientist job can be an intimidating task as there can be many things to take care in an interview process — right from justifying the practical knowledge to sh...Read More
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Applying for a data scientist job can be an intimidating task as there can be many things to take care in an interview process — right from justifying the practical knowledge to showcasing the coding skills. While we have earlier discussed articles on how to crack data science interview and what are the things to keep in mind while appearing for an interview for data science-related roles. This article deals with some of the things that you might be doing wrong if ever you are rejected in a data science interview.
Here are five things you may have been doing wrong:
Not focusing on the job description: The definition of data science jobs is not always the same and may mean different roles and responsibilities for different companies. Some of the commonly required skills may be a PhD in statistics, Excel skills, machine learning generalist, Hadoop skills, Spark skills, among others. The job description largely varies for every company and it is important to thoroughly dig it and carefully look for specific skills, tools and languages. It is important to display the skills that the potential recruiter is looking for so that they can shortlist you easily.
No specific distinction of technical skills: The technical skills in data science and analytics industry is quite wide and not mentioning your strengths correctly might jeopardise your chances of cracking the interview. For instance, it might not be apt to just say machine learning skills as it might include a whole spectrum of things ranging from linear regression to neural networks. And these sub-areas might further require knowledge of specific tools and software such as Python, Keras, R or Pandas. It is always advisable to give specific skills that you master than describing generic skills as might confuse recruiters of the exact skills that you pose.
Incorrect information and rephrasing work experience: To suit the data science job roles, many a times candidates rephrase their previous work experiences such as in the IT or software domains to present it as data science job roles, which might disguise your abilities initially but expose the depth and understanding of the skills later. You might have included job description aligning in a way that suits data science job roles but you might not have a deeper experience in it, which may get noticeable by recruiters during a one-to-one interaction. Mentioning of incorrect or misleading facts may also lead to recruiters rejecting you. For instance, the resume may state achieved an accuracy of say 90% on the test run, but what are the baseline and state-of-the-art score for this dataset to claim these numbers?
No mention about the projects that you have worked on from the scratch: Many times the only projects that a candidate mention in a resume are the ones they have done on Kaggle. While Kaggle is a platform for a lot of researchers to explore avenues in data science, it also serves as a source of practice for people who aren’t a pro in data science field and are trying to make a transition, mentions a recruiter in one of the forums. There are different kinds of the audience at Kaggle such as those who are playing around with the dataset or getting to know how problem-solving in data science works like, without having actual experience in solving or creating a new data science problems. So, listing just Kaggle project might be good but not definitive of how good your data science skills are. Even if it a Kaggle project, it is better if it is done from scratch. Other than that, it is important to mention the projects that you have worked on. It gives recruiters a chance to understand the problems you faced and the way you approached the problem, thereby giving them a glance at your problem-solving abilities.
The resume is full of buzzwords and no concrete proof of your skills: While the resume may suit the job description, but there are chances that you are rejected if there are too many buzzwords in the resume and no concrete way to prove that you actually pose those skills. You may mention in the resume that you have had experience with Hadoop, Excel or certain areas, but if you have showcased it real-time on platforms such as GitHub, it convinces the potential employers of the skills you have. They can look through various projects you have been a part of and see how you have dealt with real data. Hiring managers like to see the time that a candidate has spent from start to finish. Having a portfolio gives recruiters just that. There may be fancy sounding terms in the resume, but if you don’t have a proof to showcase it, you might be rejected for a potential data science job role.
Android is the world’s most popular mobile OS in the mobile market. From phones and watches to cars and TVs, customise your digital life with Android. Many companies preferred Android to begin mobile application development, or entering to the mobile development market because it has a lower cost barrier than iOS.
Android is an open source software stack for a wide range of mobile devices and a corresponding open source project led by Google. The Android Open Source Project (AOSP) repository offer the information and source code you need to create custom variants of the Android stack, port devices and accessories to the Android platform, and ensure your devices meet compatibility requirements.
Now, it’s time to find and hire a developer to turn your creative and amazing ideas into a tangible app. Here’s a look at what Android developers do so you’re prepared to hire the best one for your Android project.
An Android Developer designs and builds advanced applications for the Android platform and has a solid understanding of the full mobile development life-cycle. Through their creations they give the companies they work for the best opportunity to reach users and make an impact worldwide.
An Android developer is in charge of developing applications for devices powered by the Android operating system. They have a strong understanding of the patterns and practices that revolve around such platform. Moreover, they ensure the best possible performance, quality, and responsiveness of the application.
An Android developer takes project specifications and turns them into a tangible application that can be submitted and published in the Google Play store. Most mobile app projects have a design phase, a development phase, and a submission process. Many Android app developers are “full stack,” handling both design, UI and app coding, but you may choose to have both a designer and a programmer on your app’s development team. Just note that UX (user experience) and UI (user interface) design are two different skill sets that are important for the success of your project. If you decide to hire separate contractors for each component, you need one for UX and one for UI.
Android developer skills are separated into three levels depending on their experience. Developers start at the junior phase for the first few years, although the number of apps they’ve developed and the apps’ complexity are far more important when you determine the right developer for your project. After working alongside more experienced developers, they move to the intermediate phase where they can work on more projects independently. After several years working with complex Android applications, a developer is considered senior level. A senior developer can not only code a project, but they can also make decisions about how to design products. All Android developers should be familiar with:
The developer you need will be determined by your project requirements. If you’re creating a new app from scratch, you’ll need a senior-level developer with the experience to take the project from the beginning and see it through to completion. Junior and intermediate level developers are beneficial for small changes, but a senior developer should review the code before it’s put into production.
To find the right freelance developer, you need to write the project with as much detail and documentation as possible. This could be better for developer to choose the right track to start the work. Android Studio makes it easy to create Android apps for various form factors, such as handsets, tablets, TV, and Wear devices.
This article shows you how to start a new Android app project or import an existing project with your developer. Two major things to learn before start to work on the project.
Define your criteria. What kind of freelance developer you need (Junior or Senior) This enables you to describe the tasks to be done with runtime alerts and notification using the Toogit Project Management Tool, this gives you some direction on development level.
Next, Evaluate what type of challenges freelance android developer may face. This evaluation is most important to write the timeline for your project.
Toogit have more experienced android developers. They should guide and develop your project with a professional way. Always remember that more experienced Freelance Android developers on Toogit may charge more even for simple requirements. If you don’t have any understanding of the development process, it might be better to stick with a senior-level developer. A senior-level developer can help guide you through the process.
If you have a smaller budget and simple bug fixes or additions, you can specify that you need a junior-level or intermediate-level developer, but remember that they may not have the skill set to see a larger project through to completion.
The final aspect of your project to mention is its duration (time and cost) it will take to complete. Android development projects can take a week, a month, six months, or more. The duration is often determined by the developer based on your project description, but you can at least provide an estimate or a deadline, if applicable.
Once you get an estimate of how long the project will take, work with your developer to break down the project into releases if you have a flat-rate cost estimate. You can break the project into phases and ask for specific deliverables by particular deadlines.
Example phases include the following deliverables:
How you can write a brief and attractive Android Mobile Application Job description and post it for free? This guide will help you. The way you write a description will determine the quality of developer that you’ll attract. It’s important to write a detailed desciription of job which helps to build the top android the developer interaction in your project and they submit proposals with fairly accurate cost and time estimates on Toogit.
The title of your project description can include the type of development that you need. You know that you need an Freelance Android developer, but do you need a designer and a programmer? Do you need someone who understands a specific framework and the latest versions of android? The title should pull best Freelance Android developers with a specific skill set.
Next, What type of application do you want developed (gaming, educational, entertainment, etc.)? If you have documentation / excel / slides / pdfs or referrence URLs that shows basic wireframes or ideas, you can include these in your project description. Describe the project in simple and straight way with key points & modules it gives a developer a good sense of the work to be done. If you need the developer to sign an agreement, you can also specify this requirement in your description.
Part of your description should also define the deliverables including any designs, APIs, and full source code that can be uploaded to the Google Play Store. The source code is usually delivered using a version control solution such as Git, and then it can be uploaded to Google Play. You might not know the skill set level that you need, but being descriptive will help providers determine if they have the right experience for your project.
Below is a sample of how a project description may appear.
Android Developer for Online Hotel Booking App
We are looking for an Android developer to design and program a hote booking app. We have ideas and documentation included in this job post, but we require a developer, designer to paint the design into a workable hotel booking app.
The perfect developer will provide us with the .apk that we can upload to Google Play (Store). All source code, assets, databases, and design will be transferred after the project is complete. We expect the project to be divided into phases/releases where the first phase includes design and assets. The 2nd phase is the development (coding), and the final phase is testing.
The estimated duration of this project is six months. We need the completed hotel booking app by <your target date>
Now a days, the popularity of scientific computing environments such as IDL, Maple, Mathematica, Matlab and R has increased considerably. Engineer simply feel more productive in such environments. One reason is the simple and clean syntax of command languages in these environments. Another factor is tight integration of simulation and visualization in Maple, R and similar environments you can quickly and conveniently visualize what you just have computed. One problem with the mentioned environments is that they do not work, at least not in an easy way, with other types of numerical software and visualization systems. Many of the environment specific programming languages are also quite simple or primitive. At this point scripting in Python comes in.
Python offers the clean and simple syntax of the popular scientific computing environments, the language is very powerful, and there are lots of tools for simulation, visualization, and data analysis programs. Python allows you to build your own Matlab like scientific computing environment, tailored to your specific needs and based on your favorite high performance FORTRAN, C, or C++ codes.
Scientific Computing Is More Than Number Crunching: Many computational scientists work with their own numerical software development and realize that much of the work is not only writing computationally intensive number-crunching loops. Very often programming is about shuffling data in and out of different tools, converting one data format to another, extracting numerical data from a text, and administering numerical experiments involving a large number of data files and directories. Such tasks are much faster to accomplish in a language like Python than in FORTRAN, C, C++, and C#.
Scripting is particularly attractive for building demos related to teaching or project presentations. Such demos benefit greatly from a GUI, which offers input data specification, calls up a simulation code, and visualizes the results. The simple and intuitive syntax of Python encourages users to modify and extend demos on their own, even if you are newcomers to Python.
Python has some clear advantageous over Matlab and similar environments:
One of the most important skills you need to build as a Python developer is to be able to run Python scripts and code. This is going to be the only way for you to know if your code works as you planned. It’s even the only way of knowing if your code works at all!
A Python script is a reusable set of code which is essentially a Python program or a sequence of Python instructions contained in a file. You can run the program by specifying the name of the script file to the interpreter.
This step-by-step will guide you through a series of ways to run Python scripts, depending on your environment, platform, needs, and skills as a programmer. When you try to run Python scripts, a multi-step process begins.
After you play around with Python on your own or in an online tutorial, I highly recommend to you to write small scripts to strengthen your knowledge. To stay motivated, choose a program that is in some way useful to you, so you can gain insight while figuring out Python. Below are a few ways you can begin to build your expert level in Python script:
First, create a very basic version end-to-end. It is much less frustrating than trying to build a super-duper version from scratch. A big plus is that you will have something you can use very fast. Then iterate and add more complex functionality one by one.
Second, decompose large problems to smaller ones by introducing functions. Small, cohesive functions are easy to understand, test and debug.
Last, but probably the most important thing to keep in mind, is practice makes perfect. Start small, be patient and practice. Happy coding!
Applying for a data scientist job can be an intimidating task as there can be many things to take care in an interview process — right from justifying the practical knowledge to sh...Read More
Android is the world’s most popular mobile OS in the mobile market. From phones and watches to cars and TVs, customise your digital life with Android. Many companies preferred Andr...Read More
Now a days, the popularity of scientific computing environments such as IDL, Maple, Mathematica, Matlab and R has increased considerably. Engineer simply feel more productive in su...Read More