We are DemandScience, a global company which never stops innovating in our mission to provide the healthiest and most predictive global B2B data and intelligence for our customers. Our clients include sales and marketing professionals at global companies. Excellent execution is in our DNA. We provide innovative AI-analytics merged with enriched data to identify your next in-market prospects and customers at scale.
THIS JOB CONTRIBUTES TO THE COMPANY MISSION BY:
Playing a crucial role in guiding statistical and machine learning techniques to analyze data, build predictive models, and develop data-driven solutions in addition to extracting knowledge and insights from complex and diverse datasets to inform business decisions and drive innovation.
Essential Job Functions âWhat Youâll Doâ :
- Has wide-range of experience, uses professional concepts and company objectives to resolve complex issues in creative ways.
- Works on problems of diverse scope where analysis of data and ML models requires in-depth evaluation of all factors including perspective from industries and technologies available to solve the problem.
- Seasoned, experienced professional with full understanding of at least one area of specialization and can resolve wide range of issues in creative ways.
- Works on problems of diverse scope where analysis of data and ML models requires identification and evaluation of all factors that impact the solution acceptance.
- Demonstrates good judgement in selecting methods and techniques for obtaining solution.
- Normally receives very little instructions on day-to-day work and general instruction on new assignments.
- Follows standard practices and procedures in analyzing data and presenting the 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.
- Develops and implements machine learning algorithms and predictive models to solve business problems.
- Applies data mining techniques to discover insights and patterns in data.
- Continuously refine and optimize models to improve performance and accuracy.
- Work on projects involving natural language processing (NLP), computer vision, recommendation systems, etc., as needed.
- Determines methods and procedures on new assignments and leads team members.
- Excellent written and verbal communication skills. Able to convey complex ideas to a broad audience of different specializations.
- Strong sense of ownership and focus on long-term usability and extensibility.
- Emphasis on exploring, experimenting, and innovating on current patterns and designs.
- A collaborative attitude, team-player, friendly, w/ passion and flexibility to learn new tools and skillsets.
Essential Qualifications âWhat Youâll Needâ:
- Bachelor's Degree in Computer Science, Mathematics, Statistics, or related discipline.
- 8+ years experience w/ Machine learning model development with expertise in at least one domain (language or visual or speech) and has implemented multiple ML-based projects including all tasks that are needed for introducing the solution in a product/ solution.
- Proficiency in languages like Python, R, and optionally Java, C.
- Proficiency in using software development IDEs like Jupyter notebook, and source code maintenance tools like GitHub or equivalents.
- Proficiency in using one or more SQL databases (MySQL, Postgres...), or NoSQL databases (Redis, MongoDB, DynamoDB...).
- Understanding and experience in applying ML libraries like pandas, scikit-learn for data analysis, and ML frameworks like SpaCy, Rasa etc.
- Worked in cloud environment (AWS, Azure or GCP) for data transportation.
- Ability to build simple data pipeline for implementing machine learning algorithms.
- Proficiency in applying one of more: classification algorithms (K-nearest, SVM, Decision trees etc.), time-series algorithms (ARIMA etc.), forecasting techniques, and an understanding of neural-network-based algorithm architectures (like RNN, LSTM etc.).
- Analytical and problem-solving skills, with the ability to work with large and complex datasets.
- Communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders.
- Has built data pipelines on cloud environment (AWS, Azure or GCP) that requires complex transformation and transportation of data.
- Has built machine learning and natural language processing models by training, hyperparameter tuning, validating, and testing models from scratch, in at least one medium complexity commercial projects.
- Understand all basic tasks associated with NLP domain.
- Has good working knowledge of applying deep learning frameworks such as TensorFlow, Pytorch or Keras and transformers libraries from open source (e.g., HuggingFace) for natural language processing tasks.
- Has good understanding of neural-network-based algorithm architectures (like RNN, LSTM etc.) and transformer architectures (like Bert and other variations).
- Has built, implemented, and maintained data pipelines on cloud environment (AWS, Azure or GCP) that requires complex transformation and transportation of data.
- Has built machine learning and natural language processing models by training, hyperparameter tuning, validating, and testing models from scratch, in more than two medium complexity commercial projects or at least one high complexity commercial project.
- Deep understanding all basic tasks associated with NLP domain with implementation experience in at least one of the following tasks: text classification, entity recognition, sentiment analysis, machine translation, conversational bots, or document retrieval using latest NLP techniques.
- Has implemented solution using deep learning frameworks such as TensorFlow, Pytorch or Keras and transformers libraries from open source (e.g., HuggingFace) for natural language processing tasks.
- Has implemented customization in standard neural-network-based algorithm and transformer architectures.
- Has implemented model validation and testing methods and understands model selection criteria based on business, real-world-data, and performance considerations.
- Understands MLOps framework and has experience in using open-source tools (like MLFlow, DVC etc.) and/or cloud-based solution (like AWS SageMaker, Azure Machine Learning, or Google Cloud AI Platform etc.).
THE GOOD STUFF!
We embrace diversity and inclusion and encourage our amazing team members at
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