Seek · 8 hours ago

Senior Data Scientist - US Remote

United States

Full-time

Remote

Senior Level

$150K/yr - $160K/yr

5+ years exp

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AnalyticsBusiness Intelligence

Comp. & Benefits

No H1B

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Responsibilities

Analyze large (and sparse) datasets to extract meaningful patterns, trends, and insights using advanced statistical methods and machine learning algorithms.

Construct and maintain data processing workflows, ensuring efficient mapping and transformation of client source data.

Perform data enrichment by sourcing additional datasets and integrating them with client data to enhance analytical depth and accuracy.

Develop complex SQL queries and Python scripts to transform and model data, tailoring configurations and fine-tuning parameters for optimal performance.

Translate business challenges into analytical frameworks, proposing and implementing data-driven solutions that have a tangible impact on our clients’ decision-making processes.

Create and maintain interactive dashboards that provide intuitive visualizations of data insights, enabling users to derive clear, actionable information.

Work closely with analytics engineers, other data scientists and business stakeholders to ensure that ML models are aligned with business goals and technical requirements

Write clear and comprehensive documentation for ML models, pipelines, and workflows to facilitate collaboration and reproducibility

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data ScienceMachine LearningPythonSQLData EngineeringScikit-learnTensorFlowPyTorchXGBoostLightGBMSnowflakeDataBricksRedshiftData VisualizationData EnrichmentInteractive Dashboards

Required

5+ years of experience in data science, with a proven track record of deploying and training machine learning models

Advanced proficiency in Python ML libraries such as Scikit-learn, TensorFlow, and PyTorch for regression, classification, clustering, and deep learning techniques

Strong understanding of gradient boosting frameworks such as XGBoost and LightGBM for building high-performance models

Strong expertise in data and feature engineering including data cleaning, normalization, transformation, and creating/selecting relevant features from raw data

Strong expertise working with large-scale datasets directly within cloud data warehouses such as Snowflake, DataBricks, or Redshift

Advanced SQL skills: joins, subqueries, window functions, common table expressions (CTEs), aggregations, complex string manipulations, stored procedures and functions

Bachelor's degree in data science, statistics, computer science, or a related field