A data science consultant helps to conduct analysis, build models, and generate insights from enterprise data. The two most common scenarios to hire a data science consultant are 1) ad hoc analysis and 2) production model development.
1. Deep dive analysis - Data scientists can help your team uncover insights from the troves of enterprise data living within your company
2. Production model development - In addition to one-off deep dives, data science consultants can provide significant leverage when you are prototyping or productizing internal or external data products
Whether you need ad hoc analysis or production model development, there are three options to accomplish your goal:
There are hundreds of data consulting firms. At Portable, we have curated a list of over 150+ data consultants that you can evaluate. Here is the complete list.
The list includes some of the largest enterprise data consultancies in the world, as well as one-person consulting agencies like The Seattle Data Guy.
If you are looking for a consultant that can build and manage custom ETL pipelines that load data into your data warehouse, Portable can help.
We build custom data pipelines so your business intelligence team can focus on data analysis.
Data science consultants help with:
Data modeling
Machine learning and artificial intelligence
Data visualization
Statistical analysis
There are 5 steps to evaluating a data science consultant:
1. Outline your data science goals
2. Write a project description or job description
3. Evaluate your options
4. Narrow down your options and check references
5. Start with a small data science project
Whenever you hire a consultant or an employee, you need to understand two things:
The value they will create
The cost
Data science consultants can create value from:
Data analytics (better decision-making)
Process automation (replacing manual business processes with technology)
Product development (generating revenue from client adoption)
Outline the specific projects you believe will create the most value and identify any vertical-specific requirements (healthcare, e-commerce, marketing, etc.).
Once you understand how a data science consultant can create value, you need to understand the cost to make such an investment.
For a full-time employee, the cost is mostly the result of salary range and benefits. When evaluating a consultant, you need to understand the project costs, hourly costs, or retainer pricing model that will be required.
Now that you understand the path to value creation and the necessary investment to make progress against your goals, you need a clear description of the role and responsibilities.
This is where a job description will come in handy.
In the job description, you should outline the job title, pay range, and business requirements. You should also consider including:
Communication skills
Years of experience with data science
Onsite vs. remote expectations
Relevant expertise with project management methodologies (agile, waterfall)
Knowledge of your technology stack and tooling (Salesforce, Zendesk, NetSuite, IBM, Oracle, SQL Server, etc.)
Technical knowledge (SQL, software development, software engineering, Unix, AWS, GCP, Azure, data engineering, information technology, etc.)
Education (if applicable - bachelor's degree, computer science, engineering boot camp, etc.)
Don't forget to check local, state, and federal laws to make sure you hire fairly and include the necessary details in your job description.
Once you understand your goals and the type of solution you want to build for internal stakeholders or end users, it's now time to evaluate your options.
Where should you start? Well, here is a list of 175+ data consultants.
Set up introductory meetings with as many companies as you can. Most of these firms have a 'Contact Us' form or a 'Schedule An Introductory Meeting' button where you can get in touch.
Within an hour, you can schedule 20 meetings.
As you start to identify the data science consultancies that are the best fit, make sure to get references, evaluate projects, and ask for testimonials and case studies.
External validation, certification, and social proof do not guarantee a great experience, but a lack of external validation likely means you should do some more research before signing up for a big project.
Regardless of the consultant you choose, it's always a good idea to start small.
If you can sign a month-to-month agreement, or work on an hourly or project-based model for a few weeks, it allows you to evaluate a few key things:
Is the consultant responsible?
Do you have a good working relationship with the consultant?
Is communication clear and effective?
Are the deliverables of high quality?
Over time, as you see success, you can always increase the scope of your relationship, or even decide to hire a full-time employee if the scope becomes large enough.
One of the most common ways to get started with a data science consultant is by building a custom ETL pipeline.
If that's what you need, Portable can help.
Here's how you get started with using Portable for custom ETL.
Create your account (no credit card necessary)
Connect a data source
Authenticate your data source
Select a destination and configure your credentials
Connect your source to your data warehousing environment
Run your flow to start replicating data from your source to your destination
Use the dropdown menu to set your data flow to run on a cadence
Portable is a cloud-hosted ETL tool (a product not a service). While we do not offer data science consulting services, we do build custom ETL (extract, transform, load) integrations on-demand for clients as part of our product offering, for free.
We have invested years in building a platform on which we can build no-code ETL integrations for clients. As a result, we can build net new custom ETL connectors in hours or days and optimize them to your requirements.
Because we specialize in ETL pipelines, you'll receive out-of-the-box notifications, data quality, and governance that you might not receive from a consultant.
As part of your data management strategy, if you're thinking about hiring a consultant or ETL developer to develop or manage data extraction workloads, let us know - we're happy to provide a second perspective.
With Portable, you'll get the same personalized experience as a consultant without paying the prices that come along with custom services.
Looking for a custom data integration? Get started with Portable today.