Troubled by AI/ML talent scarcity in GCCs? Source expert data scientists

If you're an IT business leader at a GCC, you’re probably feeling the pressure of AI/ML talent scarcity right now. You have the roadmap, the budget, and the tools but when it comes to hiring skilled data scientists or machine learning engineers, things start to break down. You post job ads, reach out on LinkedIn, maybe even onboard a few profiles, but nothing seems to stick. Candidates aren’t matching your standards, timelines stretch endlessly, and your digital transformation goals take a hit.

The problem isn’t just a lack of resumes it’s a lack of relevant ones. You’re not alone. Across multiple GCCs we've worked with, from global consulting giants to fast-scaling fintechs and AI-first health tech companies, this problem is a recurring blocker. And it’s no longer just a hiring issue. It’s now a business performance issue.

But here’s the good news you can source expert data scientists without wasting months in the process. And I’m going to show you exactly how we’ve helped other companies like yours do just that.

Why AI/ML Talent is So Hard to Hire in GCCs (Even with In-House

Recruiters)

You’ve probably noticed that even with internal HR and hiring teams, the hiring cycles for AI/ML roles stretch for weeks, often months. And the candidates that do make it to the interview stage often fall short on real-world experience, domain knowledge, or cloud environment adaptability like AWS or Azure.

Here’s what’s really going on:

• You’re competing with global tech giants like Google, Meta, and OpenAI for a very limited talent pool.

• Local data science talent in GCCs is limited, and often early-stage or academic-focused.

• Remote candidates are hard to vet, especially if your in-house recruiters aren't deeply familiar with tools like TensorFlow, PyTorch, NLP frameworks, or data pipeline infrastructures.

• Niche skills like MLOps, LLM fine-tuning, and Generative AI deployments on cloud aren’t covered by most resumes.

Now imagine you’re trying to build or scale a team with 5 to 20 such roles. It’s not a hiring project anymore it’s a strategic operation.

That’s exactly where we come in.

Here's How We Help GCCs Source Expert Data Scientists (With

Results in Weeks, Not Months)

When one of our clients a 2,000+ employee BFSI GCC based in Pune and Hyderabad came to us, they had been trying to hire 7 Machine Learning Engineers and Data Scientists for over 10 weeks. Internal recruiters had leads, but not pipeline. We stepped in and delivered 5 offer rollouts in less than 18 business days.

What changed?

• We don’t just post jobs. We source directly from pre-vetted data science talent pools already assessed on real-world datasets.

• We understand your tech stack. Whether you’re building AI models on AWS SageMaker, or integrating LLMs with Salesforce or SAP, we match talent accordingly.

• We deploy specialist recruiters, not generalists. Our recruiters come from tech backgrounds and understand frameworks like NumPy, Spark, Vertex AI, or Databricks.

If you’re scaling your data team and tired of wasting time screening irrelevant candidates, let us do the groundwork for you.

Talk to a specialized recruiter now Fill our quick form and we’ll respond within 4 hours.

The Real Cost of AI/ML Talent Scarcity (And What It’s Doing to Your

Product Roadmap)

Let’s say you delay hiring a Lead Data Scientist by 60 days. That’s:

• 2 sprints lost.

• 1 model not trained.

• Delayed launch of a GenAI-powered feature your leadership wanted this quarter.

• Burnt-out developers trying to do data science they’re not trained for.

We’ve seen clients burn millions in opportunity cost because they waited too long, tried too many hiring portals, or couldn’t evaluate if the candidates could scale solutions across Azure ML or AWS S3-integrated environments.

AI/ML talent isn’t just expensive it’s essential. And every delay widens the competitive gap.

How to Source Expert Data Scientists in 2025 (What Works and

What Doesn't)

The hiring playbook has changed. Here’s what’s not working anymore and what is.

What’s NOT Working

• Generic job boards. Most ML resumes here are outdated or academic.

• In-house tech recruiters with no AI/ML hiring background.

• LinkedIn outreach without context or specialization.

• Trying to convert backend engineers into data scientists.

What IS Working

• Partnering with a recruitment agency that specializes in AI/ML roles.

• Using custom assessments focused on real-world project tasks.

• Sourcing talent experienced in cloud platforms like AWS, Azure, GCP, and modern data stack tools like Snowflake or Airflow.

• Hiring for role-specific outcomes: LLM ops, recommendation engines, time-series forecasting, NLP integrations with CRMs.

Check out our article on How to Hire or Recruit SAP Consultants in India useful if your AI use cases are integrated with SAP modules.

What Kind of AI/ML Talent Do GCCs Actually Need in 2025?

If you’re thinking of “just hiring a data scientist,” think again. The modern AI/ML ecosystem has evolved. Today’s GCCs need a hybrid blend of specialists depending on their current AI maturity.

Here’s a breakdown of the most in-demand roles:

Role	Key Skills	Where We Source From
Data Scientist (Mid/Sr)	Python, Pandas, Scikit-learn, AWS ML	Product startups, AI consultancies
Machine Learning Engineer	TensorFlow, PyTorch, Kubernetes, Docker	MNCs, GenAI teams
MLOps Engineer	CI/CD, MLflow, Airflow, Kubeflow	DevOps + AI backgrounds
NLP Engineer	BERT, LLMs, LangChain, Vector DBs	Research labs, FinTechs
GenAI Specialist	Prompt Engineering, OpenAI APIs, RAG pipelines	GenAI startups, R&D teams

We’ve placed every one of these profiles. In fact, we recently helped a US-headquartered SaaS company build its entire LLM team in Bangalore using hybrid hiring combining in-office and remote talent across time zones.

Strategic Hiring: Should You Go Remote, Hybrid, or On-Site?

Let’s talk structure. A lot of our clients in GCCs ask: Should we hire on-site in India, or tap into global remote AI/ML talent?

Here’s what we usually advise:

• If you need fast deployment + team collaboration: Go for hybrid in Tier 1 cities (Bangalore, Hyderabad, Pune).

• If you want deep R&D/LLM specialists: Consider remote-only hiring from research zones like Eastern Europe or South Asia.

• For enterprise integrations (Salesforce AI, SAP BTP, etc.): Focus on India-based domain experts familiar with those ecosystems.

We’re already helping clients with this through hybrid models.

Need help with global executive tech hiring too? Read Tech C-Suite Recruitment: Hiring a CIO in the Digital Age.

FAQs: What Hiring Managers Ask Before They Hire Data Scientists

How long does it take to hire a skilled AI/ML engineer through your firm?

It typically takes us 12–18 business days from requirement to offer rollout. We already maintain a pipeline of screened candidates.

• Can you help with hiring data science leaders or directors?

  Yes. We specialize in C-suite hiring too. Whether it’s a Head of AI, Chief Data Officer, or VP of Engineering, we’ve got you covered.

• Do you provide technical vetting or only sourcing?

  We provide end-to-end hiring support, including technical assessments, pre-screened resumes, domain-aligned evaluation, and interview coordination.

• Do you work with GCCs in Tier 2 cities as well?

  Absolutely. We have placed candidates in GCCs located in Coimbatore, Indore, Nagpur, and Jaipur often faster than Tier 1 cities due to reduced hiring competition.

Don't Wait. Start Hiring the Right AI/ML Talent Today.

If your internal teams are struggling, if timelines are slipping, and if your leadership wants to accelerate AI adoption in 2025 don’t wait.

Submit your hiring request now and let our team of AI/ML recruitment experts help you source exactly the talent you need.

We’re already helping GCCs in BFSI, HealthTech, Retail, and SaaS domains overcome the AI/ML hiring bottleneck. We know what it takes and we’re ready to help. AI/ML talent scarcity isn’t going away in 2025. But it doesn’t have to slow you down either.

When you partner with a recruitment agency that understands tech deeply that can speak your language (whether it’s SageMaker, Azure ML Studio, or NLP on SAP HANA) you get more than candidates. You get clarity, speed, and confidence.

Let’s help you build the data science team you need to scale AI across your GCC.

Hire Expert Data Scientists Now Talk to a specialist within 4 business hours.

FAQs -

• What does a data scientist actually do in an AI/ML role?

  A data scientist develops machine learning models, analyzes large data sets, and builds AI solutions that help businesses make smarter decisions. In GCC sectors like fintech, oil & gas, and retail, they work with platforms like AWS, Azure, and tools like Python, TensorFlow, and SQL to build scalable, predictive solutions.

  
  

• Why is it so hard to hire AI/ML experts in the GCC region?

  There’s a global talent crunch in AI/ML, and the GCC faces additional challenges like limited local talent, visa restrictions, and fierce competition from global companies. Most companies are looking for candidates skilled in cloud platforms (AWS, Azure), Python, ML algorithms, and business domain knowledge, which narrows the talent pool.

  
  

• Which programming languages are must-haves for data

  scientists today?

  The most in-demand languages for AI/ML data scientists are Python, R, SQL, and Scala. For enterprise AI integration, familiarity with Java, Spark, and tools like Hadoop or Kafka can also be highly valuable especially for large-scale projects in sectors like oil & gas or finance in the GCC.

  
  

• Can a staffing agency really help hire AI/ML talent for GCC

  projects?

  Yes, recruitment agencies with global tech expertise specialize in sourcing GCCs data scientists AI ML talent including AI engineers, ML specialists, data scientists, and even leadership talent like Chief Data Officers (CDOs). They have access to international candidate networks and understand relocation, remote hiring, and GCC compliance.

  
  

• Which industries in GCCs are actively hiring GCCs data scientists AI ML talent to drive innovation and digital transformation?

  AI/ML hiring is booming in banking, energy, logistics, e-commerce, healthcare, and government innovation sectors across the GCC. Companies use AI to optimize supply chains, automate customer service with NLP, and make data-driven investment or risk decisions.

  
  

• What cloud and enterprise technologies should AI talent be

  familiar with?

  Today’s top AI/ML talent is expected to know AWS SageMaker, Microsoft Azure ML Studio, Google Vertex AI, and data tools like Power BI, SAP HANA, or Salesforce Einstein. These skills help integrate machine learning with enterprise-grade applications.

  
  

• How long does it usually take to hire a data scientist in the GCC?

  Hiring timelines can vary between 3 to 8 weeks, depending on the skill level, visa processing, and whether the candidate is local or being relocated. Working with experienced recruiters speeds up hiring by pre-screening candidates skilled in AI, ML, cloud computing, and data engineering.

  
  

• Can GCC companies hire remote AI/ML experts instead of

  relocating them?

  Yes, many GCC firms now hire remote AI/ML teams from tech hubs like India, Eastern Europe, and Southeast Asia. With secure cloud access via AWS, Azure, and GCP, and strong collaboration tools, remote teams deliver effectively without being on-site.