Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and execute scalable and dependable strategies to facilitate or automate decision-making processes throughout the organization.

• Utilize a variety of data science methodologies and tools, coupled with subject matter expertise, to address challenging business issues and situations where the solution is not immediately evident.

• Obtain data by constructing the necessary SQL/ETL queries and import routines through various company-specific interfaces to access S3, RedShift, and Spark storage systems.

• Examine data for trends and assess validity by analyzing univariate distributions, investigating bivariate relationships, applying suitable transformations, and identifying the source and significance of anomalies.

• Develop models employing statistical, mathematical, econometric, network, social network, natural language processing, machine learning, genetic algorithms, and neural network methodologies.

• Assess models against alternative methods, expected versus actual outcomes, and other key performance indicators defined by the business.

• Execute models that meet evaluations of computational requirements, accuracy, and reliability of the relevant ETL processes at different production stages.

• Implement and deploy cutting-edge machine learning algorithms under Generative AI, create prototypes, resolve customer issues, and investigate new solutions.

• Collaborate closely with customers and the academic community to foster innovation and provide customized data science solutions.

⛳️ Requirements

• Over 10 years of experience as a data scientist, with a demonstrated ability to solve intricate business challenges using data science.

• Bachelor’s degree in Statistics, Applied Mathematics, Operations Research, Economics, or a related quantitative discipline.

• Proficient in data querying languages (e.g., SQL) and scripting languages (e.g., Python), or statistical/mathematical software (e.g., R, SAS, Matlab, etc.).

• Background in statistical models (e.g., logistic regression, supervised learning techniques) and a strong grounding in machine learning methodologies.

• Exceptional communication skills with non-technical executive audiences, capable of translating complex models and findings into clear, actionable insights.

• At least 1 year of practical experience with AI/ML technologies and contemporary machine learning frameworks.

• Proven leadership and technical mentoring experience within a team or organization.

• Strong stakeholder communication abilities, able to convey technical details across diverse audiences.

• Regular, expert-level engagement with AI-forward coding tools such as Claude and Cursor.

• Outstanding problem-solving capabilities and the ability to navigate highly ambiguous technical and business challenges with sound judgment.

• Familiarity with advanced machine learning frameworks and cloud-based data science platforms is advantageous.

🏝️ Benefits

• Health insurance

• Professional development opportunities