Data Scientist

Role: Data Scientist

Location: Remote-will work for a US client with teams based in Los Angeles, California Level: Senior

Department: Engineering

Summary

Our client is a billion-dollar lifestyle e-commerce company with over 1 million subscribers. They are looking for a Data Scientist to join their highly visible and impactful Data Team. As a Data Scientist, you will be responsible for extracting insights and knowledge from large and complex datasets to drive data-driven decision-making and solve challenging business problems. You will collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to develop and deploy innovative data models, algorithms, and predictive analytics solutions. This is a hands-on role that requires strong analytical, technical, and communication skills.

What you’ll do:

- Data Analysis and Modeling: Conduct exploratory data analysis, identify patterns, and develop predictive and prescriptive models using advanced statistical and machine learning techniques.
- Data Mining and Cleaning: Identify relevant data sources, extract, transform, and load (ETL) data from various systems,

and perform data cleaning and preprocessing to ensure data quality and integrity.
- Algorithm Development: Design and implement algorithms and statistical models to solve complex business problems, such as customer segmentation, churn prediction, recommendation systems, fraud detection, or demand forecasting.
- Model Evaluation and Validation: Evaluate the performance and accuracy of models using appropriate metrics and validation techniques. Continuously refine and improve models based on feedback and real-world data.
- Data Visualization and Reporting: Present insights and findings to stakeholders in a clear and concise manner through visualizations, reports, and presentations. Communicate complex technical concepts to both technical and non-technical audiences.
- Collaboration and Cross-Functional Support: Work closely with data engineers, analysts, and business stakeholders to understand requirements, identify data needs, and provide support and guidance on data-related initiatives.

Your background and skills will include:

- Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's or Ph.D. in a relevant discipline is preferred.
- Strong background in statistics, mathematics, and machine learning. Familiarity with various statistical techniques (A/B

testing, Hypothesis test), predictive modeling (e.g. decision trees, time series, segmentation, Xgboost), and optimization algorithms.
- Proficient in programming languages such as Python or R, with experience in using data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy) and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib) and SQL databases for data querying and manipulation.
- Solid understanding of data preprocessing techniques, feature engineering, and model evaluation methods.
- Strong problem-solving skills and ability to think analytically and creatively to tackle complex business challenges.
- Excellent communication skills, both written and verbal, with the ability to present technical concepts to diverse audiences.

These are big plus:

- Experience working with large datasets and distributed computing frameworks (e.g., Hadoop, Spark)
- Knowledge of cloud platforms (e.g., AWS, Databricks, S3, Azure, EMR, SageMaker) and experience with deploying models in a production environment
- Familiarity with domain-specific tools and techniques, such as recommendation system algorithms, natural language processing (NLP), or computer vision.