Staff Data Scientist
Staff Data Scientist
San Francisco Bay Area, California
Executive Alliance is pleased to represent our client who is the incubation arm for the world's largest company and #1 on the Fortune 500. They are transforming the customer e-tail/retail experience for future generations with a focus on health and wellness.
They are seeking a Staff Data Scientist to work out of their San Bruno, CA HQ or the New York Metropolitan area or Seattle, WA regions.
This is hybrid with presence in the San Francisco, CA or New York/New Jersey or Seattle, WA metropolitan regions. This is not a fully remote role.
This compensation for this role is:
- $200-230K base
- 25% annual bonus
- Equity included ($100k), vests over 4 year schedule
NO C2C's, agencies or international candidates, please. Only U.S. candidates in the aforementioned areas will be considered.
This incubation division was formed in 2017 as part of the company's larger innovation mission to shape the future of commerce. They pursue big ideas and take risks by stepping outside of the company's core business to focus on leapfrog capabilities across conversational commerce, mixed reality, in-store digitization, and more.
Their ultimate goal: fuel the company's core business, create new operational efficiencies, and unlock amazing experiences for our customers in the long term.
This team is working on healthcare innovations because of the company's promise is to help its customers save money and live better. This includes building products that enhance both their physical and emotional wellbeing.
About the Role:
As a Staff Data Scientist for one of their portfolio companies, your focus will be finding trends in data sets and developing next-generation algorithms to make the data useful for projects within their incubator to create new customer experience. Reporting to the Senior Manager, you will partner with engineering, product, business, UX/UI, and operations. You will need to be a self-starter with a bias for action and excellent communication skills. This is a rare opportunity, moving at the speed of a start-up, with the backing and in house data (lots of data) of a Fortune 100 company. You will bridge the art of what’s possible across today’s rapidly evolving consumer & food landscape.
Salary : $200000 - $240000
What You’ll Do:
- Data Strategy: Understands, articulates, and applies principles of the defined strategy to business problems.
- Data Source Identification: Supports the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.
- Problem Formulation: Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.
- Analytical Modeling: Selects appropriate modeling techniques for complex problems with large scale, multiple structured and unstructured data sets. Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Creates continuous, online model learning along with iterative model enhancements. Develops newer techniques (for example, advanced machine learning algorithms, auto ML) by leveraging the latest trends in AI/ML to train algorithms to apply models to new data sets.
- Model Assessment & Validation: Identifies the model evaluation metrics. Applies best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles.
What You’ll Need:
- Master’s or PhD degree in STEM or relevant field; Math, Statistics, Data Science, Analytics, AI/ML, Computer Science, Software/Data Engineering, or a related field.
- 5+ years’ professional experience in applying statistical and machine learning techniques such as hypothesis testing, time series analysis, classification, regression, and clustering to business problems.
- 5+ years’ professional experience in performing data extraction, manipulation, and visualization using programming languages (e.g., Python), scientific computing languages (e.g., R, MATLAB), or SQL.
- Extensive experience with machine learning and deep learning packages (scikit-learn, lightGBM, Tensorflow, or PyTorch).
- Experience with at least one programming language (e.g., Python, Java, C++).
- Experience in presenting findings from statistical and machine learning methods to diverse audiences through effective communication.
- Experience in executing the full life cycle of projects through project planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners.
- Proficiency in data structures and algorithms.
- Excellent in dismantling business problem/question, complex or simple, into required information/analysis and action that can address the problem/question.
- Thrives in fast-paced start-up environment, including balancing multiple projects and dealing with ambiguity.
Perks and Benefits
Beyond competitive pay, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, options for hybrid and flexible schedules, and much more.