Data Scientist

2 days ago

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Crystal Equation Corporation

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Staff Augmentation • Permanent Staffing • Statement of Work • Relationship Based Recruiting Staff • consulting

201 - 500

Description

• You will be a part of a highly cross-functional team working amongst other data infrastructure and security engineers. • You will lead end-to-end impactful data-centric initiatives prioritized and supported by the org leaders. • With the foundation analytics already in place, you will take a deep dive to discover novel insights across infrastructure, security, products, operations and more. • Gather technical and business requirements alongside cross-functional, internal engineering teams. • Discover and explore datasets suitable for the project requirements. • Perform in-depth data mining to extract actionable insights and drive strategic decisions. • Recognize patterns and anomalies in data, interpret trends, events, and propose recommendations. • Pose hypotheses, conduct research with the use of statistics, enrich data with new features, test and interpret experiments. • Design and develop impactful and actionable metrics. • Collaborate with data engineers on data acquisition and modeling. • Clearly present insights and recommendations based on quantitative research. • Independently manage, prioritize and deliver project milestones to ensure on-time completion. • Cultivate client relationships and promote collaboration. • Participate in roadmap development to grow the maturity of the data domain within the company.

Requirements

• Master’s or PHD in Computer Science, Math, Statistics, or other quantitative field • Strong written and verbal communication skills • Strong critical thinking and problem-solving skills • 10+ years of experience with SQL and Python • 10+ years of experience with metric design, data mining, feature engineering • 10+ years of experience leading multiple complex analytics and data science projects • Proficiency in utilizing statistical methods • Proficiency in implementation and optimization of machine learning models • Proficiency with data exploration, manipulation and transformation tools and libraries (Jupyter, Pandas, Numpy, Matplotlib) • Familiarity with data visualization tools such as Tableau, Power BI • Familiarity with project management tools and agile/scrum development methodology and rituals (Jira, Sprint)