Job Description
Join Meridian Analytics as a Data Scientist and be at the forefront of transforming raw data into actionable business insights. We are a leading technology company pioneering data-driven solutions for Fortune 500 clients across healthcare, finance, and e-commerce sectors.
In this role, you will collaborate with cross-functional teams including engineers, product managers, and business stakeholders to develop and deploy machine learning models that drive strategic decision-making. You will have access to cutting-edge tools, massive datasets, and a culture that celebrates innovation and continuous learning.
We offer competitive compensation, comprehensive benefits including health insurance, 401(k) matching, unlimited PTO, remote work flexibility, and generous professional development budgets.
Responsibility
- Develop and implement advanced machine learning algorithms and statistical models to solve complex business problems
- Perform exploratory data analysis and feature engineering to uncover hidden patterns and trends in large datasets
- Collaborate with engineering teams to deploy models into production environments and monitor performance
- Present findings and recommendations to stakeholders through clear data visualizations and executive-level presentations
- Design and execute A/B tests and experiments to validate hypotheses and optimize business outcomes
- Mentor junior data scientists and contribute to building a world-class data science community
- Stay current with emerging technologies and industry best practices to drive innovation
Qualification
- Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field
- 3+ years of professional experience in data science or machine learning roles
- Proficiency in Python and R with experience using libraries such as Scikit-learn, TensorFlow, and PyTorch
- Strong SQL skills and experience working with big data technologies (Spark, Hadoop, or similar)
- Solid understanding of statistical concepts, hypothesis testing, and regression analysis
- Excellent communication skills with ability to translate technical findings for non-technical audiences
- Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices is a plus
- Portfolio of published research or open-source contributions is highly desirable