Four Key Areas To Consider When Building An Outsourced Data Scientist Team

Clare Anderson
03rd February 2021

Data science outsourcing has seen significant growth over the last few years and, according to Grand View Research, Inc., the global market size for data analysis is expected to expand at a CAGR exceeding 22.8% from 2018 to 2025. Digital transformation is one of the most competitively advantageous areas you can invest in - making the most of your data and unlocking its power is essential for companies wanting to stay on top of their game. Outsourcing with a trusted partner will give you access to experts who build solutions, perform analytics and help to generate valuable business insights. Data management outsourcing should form a key part of your risk management strategy - most especially if you lack the in-house resources you need. Hiring a team of outsourced data scientists will offer you access to experts in the latest technologies and approaches and it’s often easier, less time consuming and more cost-effective than building your own team from scratch. 

So how do you ensure your data management outsourcing keeps risk mitigation and BCP objectives top of mind? Here are four key areas to consider:-  

  1. ESSENTIAL DATA SCIENCE OUTSOURCING PARTNER CRITERIA:
    • Can they demonstrate they have access to a large data science talent pool and have an EXCELLENT employer reputation in the internal job market? This is vital for ensuring they are able to attract and retain the very best talent for you.
    • Do they specialize in attracting STEM graduates who can easily be nurtured and grown into the Data Science team you need?
    • Will they assign a dedicated person to help you evaluate your team’s performance, bridge skills gaps, do due diligence and scale your team depending on your current project needs and economic situation? (You need to do the same from your side.)
    • Do their corporate culture and values align with yours? 
    • Do they have a robust data security policy?

  1. MAKE SURE YOU CONSIDER ALL THE ROLES NEEDED

    1.  
    For your outsourced Data Science team to be fully-fledged and effective, you need to hire the following key roles:

    • PROJECT MANAGER - oversees the project and is responsible for the entire business intelligence development and maintenance;
    • DATA SCIENTIST(S) - build different data models;
    • DATA ENGINEER(S) - collect data and prepare production pipelines;
    • SOFTWARE DEVELOPER(S) - implement a custom Data Science solution, do API integrations and create machine learning algorithms.

    All these roles are optional and will change depending on your current goals. For example, some Data Science teams will involve a Business Analyst and a QA Engineer, whilst others merge Data Engineer and Developer roles. You may choose to hire a dedicated team of Data Scientists and Software Developers to carry out a specific project like developing a data analytics solution. Or you may choose to expand your internal team with outsourced professionals who offer a high level of expertise in fields like AI or machine learning. As there are many options for a Data Science team configuration, you must liaise closely with your data management outsourcing company to decide which structure to follow.


  2. MERGE YOUR ONSHORE AND OFFSHORE OUTSOURCED TEAMS

    Actively involving all of your internal stakeholders with your outsourced team on a daily basis is essential to ensuring your digital transformation proceeds as smoothly as possible. Data Science often revamps processes and changes work environments and core operating methods in multiple departments. Onshore team members know best which questions to ask and what kind of data they need to support their decision-making processes - so involve them early to ensure you set off and keep on the right track. Research your data management outsourcing partner thoroughly to ensure regular communication, updates, meetings and reporting between all teams are guaranteed. A proactive change management approach is a vital part of your overall risk management strategy.

  3. TRAINING

Ensure that training for your outsourced Data Science team is a key part of the partnership you enter into with a data management outsourcing company. This can include knowledge sharing sessions and workshops; weekly meetings; hackathons and masterclasses. Make sure that knowledge sharing business trips can be arranged between two or more locations when possible. These will help to keep your distributed onshore and offshore teams synced and on the same page, as well as boost overall team morale and foster collaboration in a friendly, open-minded, and culturally diverse environment. You may also like to consider purchasing online courses (and putting them as KPIs) to help keep your team up to date in a rapidly changing environment.

 

Like most STEM jobs, there is a critical global shortage of Data Science talent so outsourcing can be a highly beneficial alternative for companies struggling to find and attract appropriate data talent onshore. Outsourcing the talent you need will also significantly cut the length and cost of the recruitment process.  Building data management outsourcing into your business continuity plan can significantly speed up your digital transformation.


If you’re looking for an outsourcing partner who will help you start fast and deliver results quickly, Sharesource could be the answer you’re looking for.  Download our eBook, '30 Essential Questions to Ask a Provider Before You Outsource’ to ensure you're informed and have the right questions to ask when considering the next step.

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