Senior Data Scientist
Role details
Job location
Tech stack
Job description
DUTIES: Design, implement, and validate advanced machine learning models for use cases such as content classification, content personalization, recommendation systems, ad targeting, chum prediction, propensity modeling, and user segmentation. Apply a range of machine learning techniques including classification, regression, clustering, Natural Language Processing, and Deep Learning. Analyze model results and partner with business teams to present insights. Partner with data engineering to integrate models into scalable production pipelines, contribute to the design of machine learning infrastructure and automation tools, ensure reproducibility, version control, and monitoring of models in production environments. Collaborate with product, engineering, editorial, and advertising teams to identify opportunities for applying data science solutions. Support experimentation and A/B testing by designing and analyzing controlled experiments. Communicate technical findings and strategy to both technical and non-technical stakeholders. Lead end-to-end data science projects: from problem definition, exploratory data analysis, model development, and validation to deployment and monitoring.
Requirements
REQUIREMENTS: Master's degree in Operations Research, Computer Science, Statistics, Mathematics, Data Science, or related field, or the foreign degree equivalent. At least five (3) years of experience with designing, implementing, and validating advanced machine learning models. Professional experience must include using: programming languages, including Python and writing complex queries in SQL; machine learning libraries, including scikit-learn, XGBoost, TensorFlow, and PyTorch to build supervised and unsupervised models; Natural Language Processing (NLP), including applying NLP techniques including multi-label text classification, named entity recognition (NER), topic modeling, and vector embeddings using libraries, including spaCy, or Gensim; data processing and ETL, including working with large-scale datasets using Dask and pandas; cloud platforms, including working in cloudbased environments, including Google Cloud Platform (GCP) or Amazon Web Services (AWS), for model training and deployment; and data visualization, including creating visualizations and dashboards using Matplotlib, Seaborn, Plotly, or Looker.
Benefits & conditions
SALARY: $139,506 - $166,077/ year, SUMMARY: Regular employees are eligible for a comprehensive benefits package including medical, dental, and vision coverage, family planning support, 401(k), paid time off, tuition reimbursement, and wellness programs.
WORK SCHEDULE: 40 hours / week (from 9 a.m. to 5p.m.)