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Job Category
Data
Job Details
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The DnA (Data & Analytics) Sales Intelligence team at Salesforce is looking for a Lead Decision Scientist to develop tools and technologies to help our Sales & Distribution team achieve extraordinary value. We are looking for someone to join our team to closely work with our business stakeholders, work on groundbreaking sales intelligent projects, to leverage massive structured, unstructured, transactional and real-time data sets from a variety of sources, to analyze usage and behavior patterns. We aim to provide actionable recommendations to enable our sales teams to increase their productivity, remove obstacles and reduce their time spend on on-sales activities.
The ideal candidate will be a key member, working closely with the Sales, Enablement, Strategy, and Operation teams to develop methods in causal inference and state-of-the-art recommendation systems. The resulting product will define the next generation of personalized productivity tools and will be essential in lifting key sales performance indicators.
If you are a statistics and machine learning whiz (a.k.a. decision scientist) who is equally at home discussing a project with business owners, researchers or developers, thrives on accelerating business growth, is willing to roll their sleeves up and do the hard work, and is extremely creative, collaborative, innovative - yet disciplined, methodical and down to earth - we want to hear from you.
Work with us as we develop and apply state-of-the-art big-data techniques, where your work will directly impact the success of Sales operations across Salesforce.
In detail you will:
- Interact with internal clients in Sales and Distribution orgs to understand their requirements for predictive analytics applications and personalized recommendations.
- Translate data insights into actions and recommendations that will drive sales performance, seller productivity, sales engagement, and program effectiveness.
- Perform advanced statistical analysis to identify enablement courses, materials, Trailhead courses, training, and other factors influencing sales productivity.
- Responsible for data mining, data science, statistical analysis including linear regression analysis, decision analysis, statistical modeling, and advanced data analysis to support operational decision making and drive business intelligence (BI) insight.
- Develop, validate, and test predictive, scalable recommendation system to be implemented as part of various internal Salesforce applications.
- Leverage mathematical principles to identify and explain data results and trends, display results, and build efficient solutions based on data results.
- Produce statistical and data analysis visuals (charts, graphs) and presentations to clearly and effectively communicate findings to internal stakeholders including senior leaders.
- Design executable and scalable experiments to quantify the impact of the recommendations.
- Understand business goals and initiatives, and combine business modeling skills with outstanding data analysis.
- Analyze and maintain sales performance metrics to identify cause-effect relationships between sales initiatives/actions and seller behavioral changes and performance uplift.
- Analysis areas might include (but not limited to): segmentation, A/B, advanced survey analysis, text mining, regressions and measurement sciences (causal inference, observational data analysis, bias mitigation, matching techniques etc.), sentiment, messaging, usage, and engagement.
- Cooperate with the Global Sales Intelligence team to design and execute replicable data acquisition and utilization processes. Acquiring, analyzing, cleaning and structuring data is an essential part of your daily responsibilities.
- Cooperate with our core data science, machine learning engineering, data engineering teams to ensure integration and implementation of the algorithms you have developed in the production environment.
In order to solve these challenges, you should be able to leverage off-the-shelf or open-source technologies as well as in-house engineering, and feel comfortable with big data solutions, applications and infrastructure:
Required Experience and Skills:
- Advanced degree in stats, math, CS or another relevant field.
- Great passion to lead technical research on bridging the understanding between business and data science.
- 5+ years of industrial experience in independently designing, implementing, and executing the sales data science projects and roadmap.
- 3+ years of industrial machine learning / statistical analytics experience including recommendation system, A/B testing, experiment design, causal inference, or quasi-experimental methods.
- 3+ Experience with engineering systems with SQL, Hive, Snowflake, and python (Sagemaker).
- Experience turning ideas into actionable designs. Able to persuade stakeholders and champion effective techniques through product development.
- Experience communicating with cross-functional stakeholders including sales, distributions, strategy, operations, data engineering, and machine learning engineering.
- Comfortable working in a dynamic, research-oriented group with several ongoing concurrent projects.
- Experience in collaborating with remote teams is a plus.
- Very strong verbal and written communication skills, excellent presentation skills, and strong influencing and negotiation skills.
- Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions.
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Salesforce welcomes all.
For Washington-based roles, the base salary hiring range for this position is $125,700 to $243,100.
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits. More details about our company benefits can be found at the following link: https://www.salesforcebenefits.com.