Company Summary

　　DISH, an EchoStar Company, is reimagining the future of connectivity. For over 40 years, we’ve been challenging the status quo and evolving our company to anticipate opportunities for business growth, industry innovation and greater customer choice.

　　Today, our brands include EchoStar, Hughes, DISH TV, Sling TV, Boost Infinite, Boost Mobile, DISH Wireless, OnTech and GenMobile. With our business reach, we cover satellite television service, live-streaming and on-demand programming, mobile plans and products, smart home installation services and, now, we are building America’s First Smart Network™.

　　Together, we'll change the way the world communicates.

　　Department Summary

　　DISH is transforming the future of connectivity. We’re doing it by building the country’s first virtualized, standalone 5G wireless network from scratch. The foundation of a connected world, it’s a network free of the limitations of the past, and flexible enough to satisfy all the social, economic and transformative needs of the changing world.

　　Job Duties and Responsibilities

　　DISH Wireless is seeking a skilled Data Scientist to join the Network Data and Analytics (ND&A) team within the Network Development organization. As a part of the br oader Wireless Data Analytics and Science team, ND&A plays a crucial role in advancing Network Quality. Positioned as the intelligence layer between lower-level data owners and data consumers, this team interprets end-to-end data across Network, Finance, and other tertiary sources, such as Legal, to establish innovative correlations that inform strategic business decisions. The organization's data insights are instrumental in optimizing resources, including finances, throughout the network build, operationalization, management, and enhancement processes. Our dedicated team of data scientists, engineers, analysts, and other members is committed to delivering the best wireless experience for both Subscribers and Enterprises.

　　In this role, you will:

　　Processing (NLP) to identify optimization opportunities, contact drivers, customer pain points, and customer/agent sentiment impact on contact outcomes

　　Develop new causal, statistical, simulation, and machine-learning techniques to explain variations in network anomalies about roaming, data, usage, and outage

　　Identify opportunities for network resource optimization in 5G SA Open RAN

　　Design experiments spanning different aspects of the network starting with construction, standing up, network linking, network turnup, operationalization, and optimization; this will be developed by working with various stakeholders with varied skillsets based on the domains they represent or own; it will also have the target state goal to optimize resources

　　Develop machine learning capabilities for Image processing to develop 2d & 3d data models

　　Driving broader correlations - actions, and events across various domains of the network for intelligent root cause analysis

　　Analyze data across multiple data sources including Financials to construe correlations to arrive at data points

　　Establish a source of truth consensus and deliver data to the users in a way that helps them make intelligent, data-backed decisions

　　Develop and execute statistical and mathematical solutions to core business problems

　　Extract, clean, manipulate, and visualize large amounts of data to deliver actionable insights

　　Produce recommendations and use statistical techniques, experimentation, and hypothesis testing to validate your findings

　　Build and productionalize end-to-end machine learning models

　　Participate in the design and architecture of ML solutions, experiments, and causal inference with the team and external stakeholders; interface with other teams as needed to resolve dependencies

　　Partner with business owners to identify areas of opportunity both within ND&A and with other departments

　　Iterate on previous models/findings to drive continuous improvements

　　Organize and present information to bring the project to life with both formal and informal presentations to large and small groups, and technical and non-technical audiences

　　Effectively communicate project statuses and key insights both within ND&A and with other departments

　　Serve as a source of knowledge for analytical/statistical techniques within the department

　　Share with, and learn from, peers to elevate others with us across the org

　　Work alongside other team members to integrate components into a finished product

　　Free up teams to focus on reporting strategy by automating repetitive tasks

　　Thrive on ambiguity and actively seek new ways to fracture the status quo and bring yourself, your peers, the organization, and the company to the next level

　　Skills, Experience and Requirements

　　As a successful Principal Data Scientist, you will have:

　　A minimum of Master’s degree in Mathematics, Statistics, Computer Science, Operations Research, or Engineering; with 10+ years of experience which is accumulated with a combination of experience and academic work

　　8+ years of experience in EDA, Modeling, and Machine Learning in R and/or Python

　　8+ years of experience with ML Ops and model deployment pipelines using tools like Dataiku, Databricks, Amazon Sagemaker, EC2, S3, Colab, Spark, Hadoop, Redshift, Snowflake, etc., actively contributing high-quality, production-ready code using - Kubernetes, Docker, Cluster frameworks, Jenkins, TensorRT, NVIDIA, MLFlow, etc.

　　8+ years of experience using ETL (Extract, Transform, Load) tools such as Python, SQL Server Job Agent, SSIS, and using SQL-based and non-SQL-based technologies, and experience with large datasets and distributed computing tools to find opportunities for product and process improvements

　　8+ years of experience that could be a combination of academia and work experience in the implementation of developing complex operations research mathematical models that utilize fundamentals from linear and non-linear programming, stochastic modeling, integer programming, and dynamic programming, for optimizing business functions that support various teams by solving such mathematical formulations using tools like CPLEX, GUROBI, GAMS and providing recommendations for making optimal business decisions

　　8+ years of experience that is a combination of academia and work experience in the development, testing, and deployment of advanced meta-heuristic algorithms like simulated annealing, tabu search, genetic algorithms, particle swarm optimization, and ant colony optimization, for finding solutions to various NP-Hard problems

　　5+ years of experience in modeling and deployment of NLP techniques like topic modeling, network graphs, and sentiment analysis, using various open source libraries including but not limited to NLTK, Spacy, Gensim, generative AI, etc, accompanied by a comprehensive understanding of and experience with recent text mining and topic modeling methods including LDA, NMF, BerTopic, word2vec, and others

　　Solid track record with the deployment of LLMs utilizing state-of-the-art tools like BERT, Llama, OpenAI, Transformers, GPT-3, Roberta

　　Extensive experience using common ML and Deep Learning frameworks such as Tensorflow, PyTorch, OpenAI, and Langchain

　　Knowledge of relevant tools like Tableau, Adobe Analytics, Salesforce, Qualtrics, and ASAPP

　　Effective use of data technologies such as AWS, Spark, Hadoop, SQL, Athena, Redshift, Snowflake

　　Ability to efficiently write complex SQL queries

　　Ability to stay up-to-date on current data science trends and be an advisor for the implementation of these trends

　　Experience mentoring and leading interdisciplinary teams of data scientists on cross-functional projects combined with an ability to communicate across all levels of the organization

　　Excellent written and verbal communication skills with the ability to write reports and procedure documents

　　Capacity to deliver a technical message to a non-technical audience

　　Positive and solution-oriented mindset

　　experience in modeling and use of discrete event simulation tools like Arena or Simio to study, identify, and distinguish between the probability density functions of the statistical distributions for optimizing business problems; use of Design of Experiments to identify conditions hypothesized to explain the variations

　　Solid foundational knowledge in the use of various statistical modeling and forecasting methodologies like time series analysis, multiple regression, Artificial Neural Networks, K-Means Clustering, K-Nearest Neighbor, Random Forest, and Decision Trees, implemented using tools like Sci-Kit learn, FB Prophet, Greykite, KATS, Merlion, NumPy, or StatsModels

　　Salary Ranges

　　Compensation: $115,500.00/Year - $165,000.00/Year

　　Benefits

　　We also offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan; all benefits can be viewed here: DISH Benefits (https://careers.dish.com/about/benefits?pk_vid=7df16cf2830b8db21671727467e02e66) .

　　The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role's location and is subject to change based on work location. Candidates need to successfully complete a pre-employment screen, which may include a drug test and DMV check.

　　This will be posted for a minimum of 3 days or until the position is filled.

　　We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer - Veteran/Disability. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. We are a true merit-based organization and work hard so there are no artificial barriers to one's potential success. DISH is committed to a workforce where everyone's opportunities are limitless.

　　Consistent with this commitment, DISH will endeavor to provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities, unless doing so poses an undue hardship on the Company, poses a direct threat of substantial harm to the employee or others, or is otherwise not required by law.