
Data Scientist II
6 hours ago
Overview
Data Scientist II at DemandScience. Join to apply for the Data Scientist II role at DemandScience.
Essential Job Functions — What You’ll Do- Apply professional expertise to develop and present solutions that have been used in the industry for similar problems.
- Work on problems of moderate scope where data analysis and ML model evaluation require considering multiple factors.
- Exercise judgment within studied practices to determine appropriate actions for given situations.
- Follow standard practices and procedures in analyzing data and presenting results.
- Work with large, structured, and unstructured datasets to identify patterns, trends, and anomalies.
- Clean, preprocess, and validate data to ensure accuracy and reliability for analysis.
- Use statistical methods and data visualization tools to interpret and present findings to stakeholders.
- Develop and implement machine learning algorithms and predictive models to solve business problems.
- Apply data mining techniques to discover insights and patterns in data.
- Continuously refine and optimize models to improve performance and accuracy.
- Contribute to projects involving NLP, computer vision, recommendation systems, and related areas as needed.
- Convey complex ideas to a broad audience of different specializations.
- Focus on long-term usability and extensibility; emphasize exploration, experimentation, and innovation around current patterns and designs.
- Performs other duties as required or requested.
- Bachelor's Degree in Computer Science, Mathematics, Statistics, or a related discipline (preferred).
- 3–4 years of building and maintaining high-quality, scalable machine learning solutions.
- 3–4 years of experience with data management, analytics, visualization, reporting, and building ML models under supervision.
- Proficiency in Python, R, and optionally Java or C.
- Proficiency in IDEs such as Jupyter and source code tools like GitHub or equivalents.
- Proficiency in SQL databases (MySQL, Postgres, etc.) or NoSQL databases (Redis, MongoDB, DynamoDB, etc.).
- Experience with ML libraries (pandas, scikit-learn) and ML frameworks (SpaCy, Rasa, etc.).
- Experience in cloud environments (AWS, Azure, or GCP) for data transportation and pipelines.
- Ability to build simple data pipelines for implementing ML algorithms.
- Proficiency in one or more: classification algorithms (KNN, SVM, Decision Trees), time-series algorithms (ARIMA), forecasting techniques, and neural-network-based architectures (RNN, LSTM).
- Analytical and problem-solving skills for working with large and complex datasets.
- Experience building data pipelines on cloud platforms requiring complex data transformation and transport.
- Experience training, validating, and testing ML/NLP models from scratch in at least one medium-complexity commercial project.
- Understanding of NLP tasks; working knowledge of deep learning frameworks (TensorFlow, PyTorch, Keras) and transformers libraries (e.g., HuggingFace).
- Familiarity with neural-network architectures (RNN, LSTM) and transformer architectures (e.g., BERT).
- Excellent written and verbal communication skills; ability to explain complex ideas to diverse audiences.
- Collaborative, team-oriented attitude with flexibility to learn new tools and skills.
- Proficiency with Microsoft Office products.
- Associate
- Full-time
- Information Technology
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