Job Title: Lead Engineer (Data Science)
Tax Term: W2/1099 Only
Location: Dallas TX - Hybrid
Employment Type: Contract

About us

Conglomerate IT is a certified and a pioneer in providing premium end-to-end Global Workforce Solutions and IT Services to diverse clients across various domains. Visit us at

Our mission is to establish global cross culture human connections that further the careers of our employees and strengthen the businesses of our clients. We are driven to use the power of global network to connect business with the right people without bias. We provide Global Workforce Solutions with affability.

Drive large-scale, high-impact data science initiatives across telecom domains, transforming raw data into actionable intelligence. This role is ideal for a hands-on leader who can blend technical depth, business acumen, and team leadership to deliver measurable value in telecom analytics, network optimization, and customer intelligence.

About the Role

As a Lead Data Science Engineer, you'll spearhead end-to-end data science projects - from ideation and model development to deployment - with a focus on telecom network analytics, churn prediction, real-time monitoring, and service optimization.

You'll lead a cross-functional team of data scientists, engineers, and domain specialists to build scalable data-driven solutions leveraging advanced analytics, big data technologies, and cloud platforms.

Key Responsibilities

• Design, develop, and deploy data science models that address key telecom challenges, including customer churn, QoS, SINR, and Video on Demand analytics.
• Lead data engineering efforts to construct robust data pipelines sourcing from telecom wireline/wireless networks and real-time data streams.
• Manage project timelines, resources, and deliverables while ensuring alignment with telecom business goals and KPIs.
• Drive collaboration among data science, engineering, and telecom domain experts, fostering innovation and cross-functional problem-solving.
• Champion best practices in model governance, versioning, testing, and code quality.
• Present project outcomes, insights, and recommendations to both technical and business stakeholders.

Qualifications & Skills

• Demonstrated leadership experience in telecom data science or analytics projects.
• Expertise in statistical modeling, machine learning, and data engineering with a focus on telecom datasets.
• Hands-on proficiency with Python, SQL, and big data ecosystems (Spark, Hadoop).
• Deep understanding of telecom data and metrics such as Wireline, Wireless, NQES, churn, and real-time performance data.
• Proven experience with Airflow, Data Proc (GCP), Vertex AI, BigQuery, and Teradata.
• Excellent organizational, communication, and team leadership skills.
• Familiarity with H2O is a plus.

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