We are seeking a Senior Data Scientist to join our Data Science team. You will play an integral part of the team, providing analytical excellence which will drive both Ria’s strategy. At Ria, your contributions can be appreciated by millions of people around the world, therefore we are looking for someone who is determined to show the world the power of applied analytics.
The ideal candidate will be passionate about asking and answering questions in large and complex datasets, and you can communicate that passion to business owners and other staff, then this is the role for you.
Responsibilities
Working on projects such as supervised & unsupervised model development.
Owning analytical frameworks that guide the product roadmap.
Designing rigorous experiments and interpret results to draw detailed and actionable conclusions.
Developing statistical models to extract trends, measure results, and predict future performance of our products and services.
Building simulations to project impact of various product and policy interventions.
Enabling objective decision making across the company by democratizing data through dashboards and other analytical tools.
Using expertise in causal inference, machine learning, complex systems modeling, behavioral. decision theory etc. to shape the future of Ria.
Presenting findings in a compelling way to influence leadership.
Supporting other projects as directed by more senior staff.
Requirements
Business acumen - understands key challenges facing our business and partners with key stakeholders to find creative ways to apply data science to solve them
Analytical skills – identify, measure, and impact the important metrics needed to manage and monitor data quality; able to simplify complex content
Attention to detail – appropriately checks all work for errors and does not let important details slip when it comes to data and its accuracy
Creative problem solving - able to use creativity and curiosity as tools to pick apart any problem, producing a solution which is relevant and realistic
Efficiency – able to quickly iterate on data generation and refinement. Looks for ways to improve processes to maximize efficiency and remove redundancy
Proactivity – acts without being told what to do at each step; generates novel ideas and processes to drive the business and team forward
Qualifications
Advanced Degree (e.g., MS, PhD, or MBA) in quantitative fields such as Data Science, computer science, Statistics, Mathematics, Operations Research or Engineering.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Strong programming skills in Python and PySpark. Comfortable in version control tools such as Git and knowledge of cloud environments such as AWS.
Experienced in working in Big Data Analytical environments/technologies (Hadoop, Spark)
Ability to write complex, efficient, and eloquent SQL queries to extract data
7+ years of related industry experience
Excellent knowledge of SQL/NoSQL, comfortable working with relational/nonrelational data models
Experience in ML Operations and model deployment is a definite asset
Excellent written and oral communication skills in English
Highly self-motivated and directed
Ability to effectively prioritize and execute tasks in a high-pressure environment