Head of Data Science

Prodapt is on a mission to accelerate connectedness, and we are looking for a visionary leader to steer our Data, Analytics, and AI/ML practice.

The Telecom industry is at a massive inflection point. With the rise of 5G, GenAI, and Edge Computing, the data landscape has never been more complexor more exciting. We need a veteran with 20+ years of experience who can turn that complexity into high-impact business value.

The Mission

As a senior leader, you will oversee enterprise-scale programsfrom building robust Data Lakehouses to deploying cutting-edge MLOps and GenAI solutions. You will be the bridge between deep technical engineering and C-suite business strategy.

What Youll Lead:

• Enterprise Transformation: Directing large-scale data engineering platform builds and AI deployments for global Tier-1 telcos.
• Domain Innovation: Identifying high-impact use cases across OSS/BSS, network telemetry, IoT, and partner monetization.
• Global Delivery: Managing world-class global teams and complex vendor ecosystems with rigorous budget and cost governance.
• Strategic Partnerships: Acting as a trusted advisor to internal leadership and client C-suites.

The Profile Were Looking For:

• Telecom DNA: Deep understanding of the telecom-technology services domain (CDRs, network analytics, etc.).
• Tech Mastery: Strong grasp of the stackSpark, Kafka, Flink, Cloud/Edge architectures, and the transition to GenAI.
• Business Acumen: The ability to build a business case that justifies the tech, ensuring every deployment delivers measurable ROI.
• Governance Guru: A solid handle on data security, privacy, and the regulatory environments that govern large-scale enterprises.

Nice to have:

Bachelors or Masters in Computer Science, Engineering, Statistics, Data Science or equivalent; an MBA or business leadership qualification is advantageous.

Enterprise data architecture & data engineering

Analytics & data science: predictive modelling, prescriptive analytics, dashboards, self service analytics

AI/ML and advanced intelligence (including model deployment, monitoring, drift, possibly GenAI) Telecom domain (network, customer, partner ecosystem, IoT/edge)

Leadership: team building, change management, global delivery model

Vendor/partner management and FinOps (cost governance for data platforms)

Stakeholder communication: business translation of analytics/AI, presentation to senior leadership

Data governance, quality, metadata/lineage, security & compliance

Cloud/hybrid/edge architecture, streaming technologies, real-time/near-real-time processing

Thanks & Regards,

Lavanya