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Hiring a Freelance AI specialist

So you are into data science and the next step is to apply AI in your business?

You will need an AI specialist, someone that, like a data scientist does, is able to identify how AI can be applied to your business and what the state of the art is.

This person will make the entire company understand and properly execute the enormous business potential of automating cognitive tasks via AI (machine learning) while mitigating the risk of wasting money on experimentation.

  • Identify the best AI (machine learning) use cases aligned to the company situation, market and product/service requirements as well as AI technology matureness.
  • Understand make-or-buy decision implications (benefits and risks), especially on internal/external processes, (marginal) costs and next AI technology shifts.
  • Identify the best suited AI provider in this field including technical diligence.
  • Plan proper execution of external providers or internal developer teams.
  • Coach the stakeholders and project teams to accumulate relevant knowledge for next AI projects.

Software Ate The World, Now AI Is Eating Software. - expert Olaf E.

The AI specialist needs to consider very different perspectives to coach companies effectively in the fields of AI/ML:

  • Understanding the business and management side as well as telling the difference between standard and more advanced AI/ML approaches that might be too early for proper implementation at large scale.
  • Make sure the company gets the highest commercial and strategic benefits from applying Machine Learning use cases.
  • Educate the stakeholders about realistic benefits, current provider and technology status as well as future shifts to be expected in the field of AI and Machine Learning.

Data is the gold of the 21st century, and data scientists are the miners. Not every day, but sometimes they come back home with pockets full of gold. - expert Denys H.

Case studies with AI specialist

Certified AI specialists in the Network

case study
AI expert case study for a telecom operator in Europe

Challenge, Context, Problems to be solved

A telecom operator in Europe planned to identify the best AI powered solution to automate relevant text and voice use cases in customer service.

Mission, tools and methodology

  • Identified the most beneficial use cases (including data / processes / stakeholders etc.).
  • Assessed the relevant providers from different strategic provider clusters.
  • Conducted proof of concepts with the most promising ones.
  • Selected the best provider based on business, process and technological requirements.
  • Planned and accompanied the implementation in production.

Achieved results

The consultant helped during the 18 months of the project to identify the relevant use cases and to find the best suited provider.

Europe
18 months
Olaf
Machine Learning Business Coach

case study
AI case study for a German hardware manufacturer

Challenge, Context, Problems to be solved

A hardware manufacturer from Germany wanted to find out when and if there are delays in ticket resolution.

Mission, tools and methodology

Within 2 months, an AI-powered solution was developed to predict ticket flow and target resolution time, based on process mining technology and machine learning. Service reps are able to anticipate delays and take measures to avoid them.

Achieved results

  • 30% reduction in resolution times through ticket flow predictions
  • 10% reduction in SLA breaches

Germany
2 months
Denys
CEO & data scientist

Must have skills for an AI Expert

  • International Management (Strategy, Innovation, Digital Transformation) skills
  • AI / ML Provider Scouting experience
  • AI / ML Business Coaching experience
  • Machine Learning modeling and engineering skills
  • MLOps (Machine Learning) frameworks knowledge
  • Data processing
  • Exploratory data analysis
  • Python, scikit-learn, pandas, SQL