Department Summary
DISH is a Fortune 200 company that continues to redefine the communications industry. Our legacy is innovation and a willingness to challenge the status quo, including reinventing ourselves. We disrupted the pay-TV industry in the mid-90s with the launch of the DISH satellite TV service, taking on some of the largest U.S. corporations in the process, and grew to be the fourth-largest pay-TV provider. We are doing it again with the first live, internet-delivered TV service – Sling TV – that bucks traditional pay-TV norms and gives consumers a truly new way to access and watch television.
Now we have our sights set on upending the wireless industry and unseating the entrenched incumbent carriers.
We are driven by curiosity, pride, adventure, and a desire to win – it’s in our DNA. We’re looking for people with boundless energy, intelligence, and an overwhelming need to achieve to join our team as we embark on the next chapter of our story.
Opportunity is here. We are DISH.
Job Duties and Responsibilities
DISH is seeking a Data Science Manager to become part of the Performance Optimization (PO) team in the Customer Experience Operations (CXO) organization. PO is a shared resource group of data engineers, software developers, data analysts, and data scientists. We provide performance measurement and reporting for CXO teams. Our focus is on establishing a source of truth consensus for data, consolidating tools and automating reporting to reduce operational complexity, and arming CXO with the data insights needed to understand the agent and customer experience to drive strategies that put DISH in a position to win.
Data scientists on this team are focused on improving DISH’s customer care experience across pay TV and wireless. This is accomplished by reducing customer effort, measured by mins/sub, building the best agent team through optimized hiring and effective goal setting, and reducing customer experience-related churn.
Types of projects the team works on include:
Text Mining: Analysis of chat/voice transcripts and IVR utterances using Natural Language Processing (NLP) to identify optimization opportunities, contact drivers, customer pain points, and customer/agent sentiment impact on contact outcomes.
Key responsibilities:
- Preemptive Customer Care – Signal Reliability: Reduce Dish TV customer churn and call minutes by proactively offering customers with signal degradation a technician visit to reoptimize their signal strength.
- Resume Parsing: Reduce agent attrition and improve contact center performance by automatically extracting pre-hire attributes from resumes to build a recommender system of which candidates to hire.
- Call-in Rate Mitigation via Customer Segmentation – Payments: Reduce call minutes and increase digital engagement by identifying customers who are making payments with agents but can use self-service options and attempt to shift their behavior.
- People leadership: Focus on the day-to-day operations of the Data Science team
- Data-driven decision-making advocate: 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.
- Strategic Collaborator: 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 CXO and with other departments. Iterate on previous models/findings to drive continuous improvements.
- Storyteller: 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 CXO and with other departments.
- Peer leader and best practice ambassador: Serve as a source of knowledge for proper 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.
- Automation expert: Free up teams to focus on customer and employee experience strategy by automating repetitive tasks.
Innovator, Trailblazer, and Disruptor: 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
A successful Data Science Manager will have the following:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Analytics, Statistics, or a related technical stream
- 2+ years of experience in people leadership
- 2+ years of experience in EDA, Modeling, and Machine Learning using R and/or Python
- 2+ years of experience with ML Ops and model deployment pipelines using tools like Dataiku, Databricks, Sagemaker, EC2, S3, etc.
- 2+ 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, etc.
- Effective use of data technologies such as AWS, Spark, Hadoop, SQL, Athena, Redshift, Snowflake
- Excellent written and verbal communication to both technical and non-technical audiences
- Positive and solution-oriented
Salary Range
Compensation: $76,300.00/Year – $109,000.00/Year
Compensation and 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.
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