The HubSpot Customer Success Strategy and Operations (CSSO) team is looking for a Data Scientist to join their rapidly growing team. This position will look to drive productivity and scale across all of Customer Success, with a focus on removing friction for their internal team and customers. In this role you’ll have to opportunity to identifying and scoping projects to enhance Hubspot’s operations, executing on these projects by performing analyses or building models and driving the lifetime value of these projects with iterative improvements.
You are someone who enjoys developing insights and recommendations from large, diverse data sets. You have a strong background in applied statistics and machine learning techniques, with a proven record developing tools and insights that drive operational change. You are able to champion these capabilities for non-technical audiences and communicate your solutions effectively. You have the desire to deeply understand both the analytical side, but also the business context and need. Ideal candidates are collaborative problem solvers who will work closely with members of Business Intelligence, Customer Success, Machine Learning, Product and Engineering teams, and Operations teams across HubSpot, including a strong partnership with your team members in Customer Success Strategy and Operations.
In This Role, You’ll Get To
- Apply your knowledge of statistics, data modeling, and machine learning, combined with exploratory data analysis to help their company achieve key business goals at scale
- Deeply understand Customer Success strategy, risks, and opportunities; Identify opportunities and generate solutions to business challenges based on analysis and modeling of large, complex data sets
- Drive efficiency gains across Customer Success functions (Account Management, Onboarding, Support), giving their frontline reps the tools they need to support the growth of their customers
- Work collaboratively with operational business stakeholders to automate and improve the efficiency and reliability of our data infrastructure, reporting, and modeling
- Partner with the Machine Learning team to understand the performance of our machine learning systems
- Build predictive models and machine-learning algorithms; Collaborate closely with internal product and engineering teams to help turn ML research prototypes into new tools or features
- Develop strategies to solve complex business problems by applying advanced data-driven solutions composed of predictive modeling, statistical methods, and cognitive computing components.
They Are Looking For People Who
- Have experience applying advanced analytical techniques, applied statistics and machine learning to drive more efficient business processes (Data Scientist, Data Analyst, Business Intelligence Analyst, etc.)
- Have strong coding skills, particularly in Python (R also considered), and advanced knowledge of SQL.
- Are educated in Computer Science, Statistics, Economics or equivalent quantitative field
- Have experience working with large real-world datasets, where raw data must be cleaned and manipulated before use
- Are experienced with a variety of ML techniques and libraries (Scikit-learn, Tensorflow, etc.)
- Are motivated to learn rapidly and expand your skillset.
- Are comfortable taking an unstructured business problem and translating it into a well-scoped analysis, or re-framing it as automation and/or Machine Learning problem
- Have the ability to adapt quickly to changing priorities; manage time, multiple tasks, and deadlines effectively
- Have proficient communication and interpersonal skills; can convey complex analyses to a broad audience
- You are great at solving problems, debugging, troubleshooting, and designing & implementing solutions to complex technical issues.
- You thrive on teamwork and have excellent verbal and written communication skills.
- You have experience as a strategic business partner, using data to drive impact and change.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1