Remote Sales Engineer Jobs in Washington, DC (NOW HIRING)

Solutions & Sales Engineer – Data Science 100% Remote (forever)We're seeking a Solutions & Sales Engineer who is ready to play a crucial role within a rapidly growing and high-performing organization, and who brings demonstrated impact selling and delivering high-tech services in financial services and/or healthcare markets. You enjoy addressing clients' most pressing and complex issues by designing, planning, and managing analytic initiatives and scoping machine-learning solutions (training or consulting) from start to finish.

You will partner with and build strong relationships with our clients' staff and management in the government and corporate sectors, providing business analytics, artificial intelligence, and IT solutions for mission-centric problems. While this is primarily a sales role, we anticipate that those applying for this position enjoy the challenge of engaging with our clients over the longer term to ensure their data and analytical challenges are well met by our company.

We are looking for staff who have or can rapidly grow into the triple-threat model of data science consulting: performing marketing and sales, providing technical competence, and delivering high-quality work.

We are a fast-growing company so the person in this role should be ready for change, wearing multiple hats and engaging regularly across internal teams. Key responsibilitiesEngage teams with diverse skills, including management consultants, software engineers, data scientists, and instructors, to sell, scope, and deliver high-quality deliverables for our healthcare clientsLead the scoping of training and/or consulting project requirements, draft proposals and analytic plans, create project timelines, and draft other materials related to sales and capture.

Help derive insightful, strategic recommendations through core management consulting skills combined with data science / machine learning applications.

Use your analytics and machine learning expertise to research and recommend the best analytic approaches to solving challenges facing our clients.

Lead and collaborate with internal and external stakeholders to manage data logistics, including data transfers, understanding data structures, business rules, etc. Create compelling presentations that provide actionable insights and recommendationsPresent reports to key internal and external stakeholders, effectively communicating the key findings and recommendations.

As you mature in the role, manage multiple projects concurrently to ensure successful completion of analytic projects.

Skills you bring5+ years of experience with Data Science, Machine Learning and/or AnalyticsMust have at least some hands on experience, or at least experience training courses on these subjectsAt least some experience with training – either selling training solutions, administering training or teaching at a university/bootcampBusiness Development, Sales and/or Marketing experience is a big plusRegardless if you have this experience or not, you must have a desire to sell as that is the primary responsibility of this role. But we find that sales is easier to train on than Data Science, which is why Data Science skills are the most important thing we're looking forThe ideal candidate will have: Experience selling to healthcare and/or financial services clientsAt least a Bachelor's degree in a quantitative discipline (statistics, economics, mathematics, computer science, electrical engineering, or a related scientific discipline).An understanding of the manipulation of data sets, both structured and unstructured, with natural curiosity for exploring data and finding the untold story.

An understanding of statistics, modeling and machine learning techniques,Hands-on experience building analytic processes and solutions.

Familiarity with the following programming languages: SAS, Python, R and SQL.Familiarity with cloud based, open source computing environment. Understanding of the best ways to display data visually, creating powerful presentations which effectively demonstrate the value of analytic deliverables.