Job Description

Company Summary:

DISH Network Technologies India Pvt. Ltd is a technology subsidiary of EchoStar Corporation. Our organization is at the forefront of technology, serving as a disruptive force and driving innovation and value on behalf of our customers.



Our product portfolio includes Boost Mobile (consumer wireless), Boost Mobile Network (5G connectivity), DISH TV (Direct Broadcast Satellite), Sling TV (Over The Top service provider), OnTech (smart home services), Hughes (global satellite connectivity solutions) and Hughesnet (satellite internet).



Our facilities in India are some of EchoStar's largest development centers outside the U.S. As a hub for technological convergence, our engineering talent is a catalyst for innovation in multimedia network and communications development.
Summary:

Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our people play vital roles in connecting consumers with the products and platforms of tomorrow.


Job Duties and Responsibilities:
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The Data Product & Monetization team

This team focuses on delivering AI and data-driven products that drive business value and monetization. The team works on high-impact initiatives involving machine learning, data science, and Generative AI, supporting enterprise-wide use cases.####

Key Responsibilities

Design and implement advanced data science solutions using classical ML, statistical modeling, and Generative AI. Build scalable data pipelines for preprocessing, feature engineering, and model training. Conduct exploratory data analysis (EDA) to identify patterns and guide solution development. Mentor junior data scientists and lead technical workstreams. Collaborate with cross-functional teams to translate business challenges into AI/ML solutions.

Skills - Experience and Requirements:
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Educational Requirements

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
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Skills and Qualifications

3+ years of experience in data science with a focus on classical machine learning and model deployment. 1+ years of hands-on experience with Generative AI (e.g., AWS Bedrock, Hugging Face, NLP techniques). Proficiency in Python for data manipulation, modeling, and evaluation. Experience with cloud-based ML workflows (AWS, GCP, or Azure) and version control tools like Git. * Strong communication and leadership skills with prior mentoring experience.