- Data Mining
DISH is a Fortune 250 company with more than $14 billion in annual revenue 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.
A successful Financial Analyst will have the following:
Bachelor's degree from four-year college or university; or three years related experience and/or training; and two plus years of experience; or equivalent combination of education and experience.
Strong analytical skills including building models, automating reports, and data mining.
Strong financial analysis foundation in creating forecasts and models.
Proficiency with analytical tools and software a plus (SQL, Tableau, Hadoop, Python, etc.).
Must possess excellent communication and presentation skills, and be comfortable interacting with management.
Effective organizational skills and eye for process improvements; Financial/Mathematical proficiency.
This Financial Analyst position reports within our Customer Retention Marketing Team; and will be responsible for analyzing and reporting on existing customer behaviors and churn.
Primary responsibilities include:
Improving churn & revenue results by analyzing customer metrics, monitoring variances, identifying trends, and recommending actions to management.
Leveraging extensive existing customer data including: viewer measurement, product engagement, profitability, and risk behaviors to support decision making and identify new opportunities.
Accessing data via SQL, Teradata, Hadoop and other tools to support analysis and reporting; reporting on performance by comparing and analyzing actual KPI results with plans and forecasts.
Creating big data models to support key initiatives, examples include: predictive churn, individual profitability, upsell propensity, next best action.
Providing creative alternatives and recommending actions by analyzing data, identifying trends, and making comparative analysis; increasing productivity by developing automated reporting and forecasting solutions.
Consult with management to guide and influence long term and strategic decision making.