Data Science/ML

Remote 9-12 Months 1099 or C2C This position may be performed remotely anywhere within the United States except for the State of Colorado, Alaska, North Dakota, or South Dakota.

We are looking for an experienced data scientist to lead the initiatives we’re taking, to improve the product offerings , from the perspective of risk modelling and business forecasting (prescriptive & predictive). As a team member in core data science team, you will own the research charter for data and decision science to enable the business stakeholders to be data-driven and deterministic, by providing insights into the decisions at-hand and roadmap planning. You will be working in a team of Data Scientists to enable a culture of 360-degree analysis of business, with ownership of the modelling environments and ML models. You will get the support to evangelize sound practices for prototyping of concepts, to fail-fast and/or maintain continuum of persistent research. You will collaborate with multi-disciplinary teams of engineers, product owners & business stakeholders to solve complex & ambiguous problems, in the domains of: Gift Cards E-Commerce (B2B & B2C) Forecasting of Inventory, Traffic & Breakage Risk Modelling (Scorecards) Fraud Detection & Prevention Loyalty & Rewards Programs Modelling Responsibilities: Partner closely with Product, Engineering, Marketing, Sales, Finance and Data Science teams to shape product strategy using rigorous scientific solutions Apply statistical, machine learning and econometric models on large datasets to: i) measure results and outcomes of our current models and product strategies, ii) optimize user experience while minimizing fraud/risks Design, conduct, and analyze experiments to quantify the impact of product and operation changes Develop metrics to guide product development, and create dashboards for key performance indicators and deep dive to understand the drivers Drive the collection of new data and the refinement of existing data sources

Requirements

Masters (or equivalent) degree in a quantitative discipline (Statistics, Operations Research, Data Science, Mathematics, Physics, Engineering etc.). A strong background in advanced mathematics, in particular statistics & probability theory, data mining, and machine learning.

5+ years of overall professional experience with 3+ years in data science, doing exploratory data analysis, testing hypotheses, and building prescriptive & predictive models.

Demonstrated experience in creation, deployment and performance evaluation of supervised and unsupervised machine learning models.

Proficiency in Python. Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL.

Strong Communication: ability to articulate clearly, navigate & adapt across different seniority levels. Ability to use statistical, algorithmic, data mining, and visualization techniques to model complex problems, find opportunities, discover solutions, and deliver actionable business insights.

Be passionate about collaborating daily with your team and other groups while working via a distributed global operating model. Be eager to help your teammates, share your knowledge with them, and learn from them.

Preferred Qualifications Experience with MLOPs frameworks Experience with creating explainable ML model Experience with source code control systems like Git Experience with data visualization and business intelligence tools like PowerBI Knowledge of experimental design and A/B testing Experience in an Agile development environment Experience with AWS cloud environment Proven ability to quickly learn and apply new techniques Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment Must be a team-player and capable of handling multi-tasks in a dynamic environment Excellent business writing, verbal communication, and presentation skills