A Company in Dallas, Texas resolves issues with machine learning and data science hiring by providing a complete solution in one package

“AI is everywhere it seems these days, but the truth is that many organizations are struggling to implement AI with success. The rate of AI project failure to be at around 70-80%. According to Gartner, 85% of Machine Learning (ML) projects fail. According to TechRepublic, 85% of AI projects eventually fail to bring their intended results to the business.” – COGNILYTICA

27 January, 2023: As companies look to leverage the power of machine learning (ML) to gain a competitive edge, the demand for skilled machine learning engineers is on the rise. However, with so many options out there, how do corporations/managers know they are hiring the right person(s) for the job? To help answer that question, we explain common problems data science implementations face. These problems are more prevalent in businesses seeking to invest in this competitive technology but lack proper data science management experience. We then explain how Superior Data Science LLC (SDS) is providing a solution to these common problems, leading to a higher return on investment. 

Problem 1: No Data Science Project Management 

When it comes to hiring machine learning engineers, many companies turn to freelancing websites or hire data scientists through recruiters. However, this can often lead to high failure rates due to the simple fact that these data science employees/ freelancers do not come with data science project management expertise. Data science energy is spent without the process of planning, executing, monitoring, controlling, and closing a project to achieve specific goals and meet specific success criteria.

Problem 2: A High Opportunity Cost of Project Churn 

Additionally, these hard-working engineers often benefit from project churn, meaning they can add completions to their project reviews or resume bullet points, even if they do not complete all the steps within the data science methodology or show profit from machine learning models. When completing this type of project, they placate management stating that all possible modeling evaluations were completed, and research into this type of AI model is simply costly and will not bear fruit. This can lead to incomplete projects and a lack of continuity for the business investment however project completion rates rise for the engineer through statements of completed project evaluation. Without proper management expertise, no one can look through the code and modeling techniques to make sure that this is in fact true. 

Problem 3: Hired Expertise comes with AI Expertise only 

Additionally, data science hiring leads to projects often lacking the necessary data engineering and cleaning for effective modeling results. Data scientists are great at modeling but 80% of the work is grueling and manual data cleaning and engineering. These engineers will have to either ask for additional help through the hiring of data engineers and analysts or take time to learn how to complete these tasks themselves, leading completion of your project without data engineering domain experience and expertise. 

Problem 4: No matter how good the AI model is, it needs a home for profitable execution

Simply put, these models require a continuous integration and development pipeline – but the truth is the data scientist knowledge base is not responsible for or an expert of dev-op or ml op pipelines. Once the modeling is complete, the hired data scientist or freelancer is now responsible for learning a whole other branch of technology. Of course, if you’re a larger firm and hire these roles out individually you’re more secure in having greater chances of higher AI success. 

To remediate the listed issues, companies have turned to Superior Data Science LLC. This organization offers a packaged deal where projects are managed effectively through a project manager, experienced data engineers, and custom devops pipelines for effective delivery. The team of machine learning engineers at Superior Data Science LLC has a proven track record of success, with years of experience in the field and a deep understanding of the latest ML techniques and technologies. They have worked on a wide range of projects, from fraud detection, image recognition to natural language processing. 

After SDS installs data engineering, AI modeling, and dev-ops pipelines through data science oriented project management, SDS can focus on hiring data scientists long term so that when the contract is completed, the receiving company continues to churn out profitable ai models effectively. One of the key advantages of hiring Superior Data Science LLC is their CEO, project manager and team lead who has an MBA, MS Finance and a technical MS in engineering, has a range of both technical and business expertise. Combined with several years of machine learning experience at reputable corporate firms such as Standard and Poors, Bell Flight, Citigroup, Propelled Brands, ETC you’re not blindly risking company budget anymore. Effective data science project management has occurred already with happy clients at the receiving end. It is no longer your responsibility to create these types of effective pipelines, but rather to implement one which has already been tested. 

In addition to their experience, the machine learning engineers at Superior Data Science LLC have strong technical skills. SDS has experts in the pythonic programming language and use well-known and tested libraries. ML frameworks such as Pytorch, TensorFlow and Scikit-learn provide you quick installation of cost-saving or revenue-producing machine learning models. They are also familiar with cloud computing platforms like GCP, AWS and Azure, as well as big data tools like Hadoop and Spark. They also know that models are just half the story, and they are experts in placing the models in continuous integration and development pipelines so that ai models execute with proper monitoring and timely execution. Another benefit of hiring from Superior Data Science LLC is the certifications their engineers hold. The machine learning engineers hold certifications to qualify their employment at Superior Data Science. These include AWS Certified Machine Learning – Specialty, Google Cloud Professional Machine Learning Engineer, and Azure Machine Learning Certification, demonstrating a connection to larger platforms and a level of knowledge and expertise with the best technologies being sold today.

Furthermore, the team’s unique combination of business acumen and technical expertise allows not only design and development of ML models but also effective communication with your business – specifically explaining the value and ROI of these models to both technical and non-technical stakeholders. Effective communication is a crucial aspect of machine learning projects. With Superior Data Science, communication is reserved to one project manager, who manages the entire engineering process on your behalf. The project manager places great emphasis on strong verbal and written communication skills, so that even non-technical stakeholders are excited, understands and forecasts the value of the completed AI model(s). Stated another way, the project manager is comfortable presenting the completed work to others so that complex ML concepts and its delivery pipeline is understood in simple terms. For every client, they provide a proposal presentation, a statement of work, project governance document, regular update documents and a final presentation.

In conclusion, while it’s true machine learning models can execute profitable actions and decision analytics at low costs, building models also comes with building multiple and complex engineering pipelines. Hiring the right machine learning engineers and other supporting professionals is vital for the success of ai projects and corresponding ROIs. Hiring blindly, places investments at risk of high failure rates due to lack of project management expertise, advanced data engineering skillsets and continuous integration/development pipelines. 

Contact details:

Name: Jobin Thomas

Designation: CEO, Data Science Project Manager

Number: +1 (214) 518 – 9248

Email: jobin@superiordatascience.com

To get a complete solution and higher chances of AI success: follow this link 

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