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Now that you’ve made it this far and have taken to heart the guidance in the chapters, let’s look at what you need to know when you’re ready to start your job quest in the data science world. Gaining some perspective of the types of job opportunities advertised may be quite useful.
In this chapter, we’ll take a look at different types of ads: namely, entry-level, experienced, and senior data scientist ads. In addition, we’ll discuss some relevant tips for online searching and present a few samples of ads for data scientist positions that are currently open.
18.1 Ads for Entry-Level Data Scientists
There are relatively few ads for entry-level data scientists, which is something of a mystery considering that a junior data scientist is bound to yield the highest ROI for a company starting a data science project. Basically, an entry-level data scientist has minimal experience and a lower level of expertise is expected (simply working knowledge of R or any other data analysis tool may be sufficient). Compensation may not reflect the amount of knowledge that is required for this position. After you gain some experience, you can proceed to more challenging roles, yielding better compensation. Here are a couple of examples of entry-level data scientist jobs so that you get an idea of what to expect, but the requirements are bound to have changed a bit by the time you read this.
Title: Junior “Big Data” Software Engineer
Summary
This position involves creating and using custom software tools to gather, manipulate, pre-process, and filter large data-sets. We’re looking for a candidate who enjoys working in a fast-paced startup environment with an interest in artificial intelligence technologies and the semantic web. This position will involve working with more senior engineers, with opportunities for mentorship and career advancement. If you are a self-motivated, highly creative, engineering-focused person, with an interest in AI and related technologies, come talk to us. If you watched IBM Watson compete on Jeopardy and thought “I want to build that,” talk to us.
Skill Requirements
- Solid understanding of Linux software development
- Experience with Linux command-line text manipulation tools
- Desire and ability to work with large data-sets
- Experience in Agile development and object-oriented design
- Basic Linux system admin knowledge
- Self-motivation & creativity
- Familiarity with multiple languages (Java, Python, etc.) is a plus.
(Source: Kaggle.com)
Title: Junior Data Scientist
Summary
This is an exciting opportunity for an experienced data and analytics professional to join a leading brand name company within an innovative and growing team. This position sits within a growing analytics function offering the chance to play a key role in the further development of customer insight and business analysis.
This role will play a key part in developing and delivering algorithms and new analytical approaches to better understand and enable pricing and business analytics. The role will involve the following key responsibilities:
- Using multiple data sets and sources to streamline analysis and generate algorithms to develop analytical frameworks
- Work closely with other internal teams and senior stakeholders to better understand and available data, with a view to identifying personalization driven products and solutions
- Develop programming language based scripts (SAS, SQL or R) to help in the creation of market leading customer insight strategies
- Work with clients to improve and build upon their understanding of their digital channels and personalization
- Mentor and lead junior team members.
Skill Requirements
To be shortlisted for this position, you must have the following ESSENTIAL skills and experience:
- Experience working in an advanced analytics function
- Strong working knowledge of SAS, R, Python or SQL for advanced statistics and programming/modeling
- Degree in a numerical discipline e.g., Math, Stats, Physics, Economics etc. from a top tier university
- Experience developing and implementing algorithms and analytic principles
- Good communication skills – ability to communicate technical strategy into easily understandable concepts.
(Source: Harnham.com)
18.2 Ads for Experienced Data Scientists
Ads for more experienced data scientists are the most commonplace. They are most often related to larger companies or startups with big funding behind them. Basically, when a company is looking for an experienced data scientist, it is data savvy and may even be data driven. Reading ads for experienced data scientists can be very educational for anyone interested in developing a career in this field because they demonstrate the skills and experience needed. Remember that these ads express what is in demand at the moment, so don’t take their requirements as gospel. Needs will change over the years as more advanced technologies come about and the data science world takes a more formal shape. Here are a couple of examples of such ads:
Title: Data Scientist
Summary
- Work on large data sets of structured, semi-structured, and unstructured data to discover hidden knowledge about the client’s business and develop methods to leverage that knowledge within their line of business
- The successful candidate will combine strengths in mathematics and applied statistics, computer science, visualization capabilities, and a healthy sense of exploration and knowledge acquisition
- Work closely with various teams across the company to identify and solve business challenges utilizing large structured, semi-structured, and unstructured data in a distributed processing environment
- Develop predictive statistical, behavioral or other models via supervised and unsupervised machine learning, statistical analysis, and other predictive modeling techniques
- Drive the collection of new data and the refinement of existing data sources
- Analyze and interpret the results of product experiments
- Collaborate with the engineering and product teams to develop and support our internal data platform to support ongoing analyses.
Skills Requirements
- M.S. or Ph.D. in a relevant technical field (e.g., applied mathematics, statistics, physics, computer science, operations research), or years of experience in a relevant role
- Extensive experience solving analytics problems using quantitative approaches
- A proven passion for generating insights from data
- Strong knowledge of statistical methods generally, and particularly in the areas of modeling and business analytics
- Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- Fluency with at least one scripting language such as Python, Java, or C/C++
- Expertise with relational databases and SQL. NoSQL is a big plus
- Experience working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive, etc.)
- Expert knowledge of an analysis tool such as R, D3, Matlab, SAS, Weka with the ability to transfer that knowledge to different tools
- Experience with Fraud analytics is a nice to have.
(Source: Linkedin)
Title: Data Scientist – London – £70,000 [Note: Though quite atypical, some ads do mention the salary.]
Summary
My client, a market leader within the market research sector with offices based worldwide is now looking to hire a talented data scientist to come on board in central London.
With medium term plans to build a data function of 10 scientists in UK and continuous learning and support from the established team in the USA, this presents an exciting opportunity to join a data oriented company with big growth plans and career progression.
Now at 3 million members worldwide, the company is generating and storing huge amounts of data on a daily basis. The successful scientist will produce statistical models and complex algorithms used for extracting, testing, hypothesizing and providing meaningful insights used to inform and make business decisions by organizations across the globe.
Skills Requirements
The successful candidate will have the following skills and experience:
- BSC/MSC/PHD with computer science, mathematics or related area
- 3yrs+ experience within a data science or analytical role
- Relevant working experience working with vast data sets
- The ability to work as an individual or as part of a team
- Extensive experience with at least one statistical language (R or Matlab preferred)
- Proficiency in at least one programming language (Python or Java preferred)
- Strong SQL skills.
Above all you must have an inquisitive nature and a real passion for data!
(Source: Linkedin)
18.3 Ads for Senior Data Scientists
Ads for senior data scientists are fewer though encountered more often than those for junior data scientists. Senior data scientists are basically the top-tier data scientists, the ones who have sailed all kinds of oceans and have fought against monsters of data. They usually end up in a business-oriented position where they deal directly with management, and often with the company’s clients, themselves. Note that if you try the freelance track, you’ll basically be taking a senior data scientist role even if you don’t refer to it this way. This is because you’ll need to undertake all the different aspects of that role including the link to the business world, the project organization, the architecture design, etc.
You’re probably not going to be hunting for this type position right now, but it’s good to be aware of what’s out there in case you want to drive towards it quickly and you have enough expertise to make it happen. Experience can be gained relatively easily once you are committed to your goal, are focused, and know what you are doing. Here is an example of a senior data scientist position from a US company.
Title: Senior Data Scientist
Summary
As a senior member of the data sciences team, you will be responsible for managing and executing critical R&D projects, while providing thought leadership, along with significant personal contributions. Working in a highly collaborative environment, you will drive product innovation and partner with Engineering and Product teams to prototype and launch data-driven features and products. You will develop deep domain expertise in digital advertising and generate key insights that influence business decisions and technological solutions. In addition, you will be active in the data sciences community and contribute to attracting, retaining and growing the best talent in a performance-driven organization.
Skills requirements
Required Qualifications
- PhD in a quantitative discipline (e.g., statistics, computer science, physics), or MS with equivalent experience
- 10+ years of hands-on experience in analysis and modeling of large complex datasets
- A passion for innovating with data sciences at scale – applying modern algorithms to massive datasets and creating measureable business value
- Excellent interpersonal and communication skills, with a strong written and verbal presentation
- Proven ability to take ownership of a project and lead R&D with minimal supervision
- Track record of successful implementations of quantitative, data-driven products in a business environment
- Deep understanding and hands-on experience with optimization, data mining, machine learning or natural language processing techniques
- Superb understanding of algorithms, scalability and various tradeoffs in a big data setting
- Expert level in R, Matlab or a similar environment; proficiency in SQL
- Ability to personally put together a system of disjoint components that implements a working solution to the problem
- Experience programming in at least one compiled language (C/C++ preferred).
Preferred Qualifications
- Experience analyzing internet scale sparse datasets (billions of rows, thousands of columns)
- Expertise in using Hadoop and/or MPP databases (e.g., Netezza, Vertica, RedShift) for complex data assembly and transformation
- Digital advertising or web technology experience
- Experience with real-time bidding, electronic trade execution or high-frequency trading algorithms.
(Source: Linkedin)
18.4 Online Job Searching Tips
Other ads for data scientist positions may masquerade as ads for different types of positions, so you may want to include the following keywords in your search for data scientist jobs online:
- Data Engineer
- Big Data (Software) Engineer
- Chief Scientist
- Senior Scientist
- Big Data Analyst
- Hadoop Programmer / Developer
- Big Data Scientist
- Big Data Analytics
- Research Scientist – Data
- VP, Data Science
- Data Mining Scientist
- Machine Learning Developer
- Machine Learning Specialist
- Statistician
In addition, if you decide to look into websites specifically designed for job hunting, it makes sense to upload your resume and keep it up to date. This will make the application process much quicker and help you target a variety of companies simultaneously. Always have someone check your resume before putting it anywhere, however, preferably a professional editor. Also, be sure to keep your LinkedIn profile in a professional state, especially if you plan to network parallel to targeting online job ads. Here are some examples of useful sites for data scientist ads:
- Indeed.com – everything on this site is about job hunting for all kinds of jobs, including data science ones.
- LinkedIn.com – there are separate groups in this social medium that act like job boards, like LinkedIn’s built-in job search function.
- DataScienceCentral.com – job-board area under Jobs option.
- Kaggle.com – primarily for data analysis competitions, this site also has a forum for data science jobs.
Keep in mind that all of these are just one strategy for landing a data science job. Don’t forget there are other paths to the same goal and make use of networking. A connection with a person working for a company you are applying to could lead to a job offer for another position if the one you are applying for doesn’t work out. So draw your own plan of action for making it happen in this fascinating field. It won’t be easy, but rest assured it is definitely worth it!
18.5 Key Points
- Familiarizing yourself with the various data scientist openings, even the ones for more advanced positions, can be very useful in your search for data science jobs.
- There are few job ads in the field for junior data scientists, at least at the present time. Most of the ads out there for data scientists are for experienced ones, followed by those for chief data scientists.
- When looking for a data science position, it’s useful to search for openings using various keywords, not just “data scientist,” as different companies may refer to the role with different names.
- It’s good to have a resume in a professional state online when searching for a data science job using a job hunting site.
- Having a presentable LinkedIn profile can help you significantly in your search for a data science position through networking.
- Some useful sites for data scientist ads include:
- Indeed.com
- LinkedIn.com
- DataScienceCentral.com
- Kaggle.com