Summary
Join Ardent as a Data Scientist and play a critical role in analyzing complex unstructured data sets, extracting valuable insights, and driving data-driven decision-making for product and service development. As a remote/hybrid position located in San Juan, Puerto Rico, you will work closely with cross-functional teams to solve challenging business problems, develop AI/ML models, and contribute to the growth and success of our company.
Requirements
- Ph.D. or Master's Degree in Data Science or a related field
- Proven experience as a Data Scientist, with 2+ years (with Ph.D) or 5+ years (with Master's Degree) of relevant work experience
- Proficiency in programming languages such as Python or R
- Strong knowledge of NLP and CV libraries (e.g., spaCy, NLTK, OpenCV) and machine learning frameworks (e.g., TensorFlow, PyTorch)
- Solid understanding of statistical analysis, hypothesis testing, and A/B testing
- Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly)
- Experience with researching and developing AI/ML models
- Familiarity with SQL and database management systems
- Strong problem-solving skills and the ability to work independently and collaboratively
- Excellent communication and presentation skills
- Attention to detail and a commitment to producing high-quality work
Responsibilities
- Conduct in-depth analysis of unstructured data, including text and image data, to identify trends, patterns, anomalies, and biases
- Clean, preprocess, and transform raw unstructured data into usable formats for analysis
- Utilize NLP and CV techniques to extract insights from data
- Research and develop AI/ML models, and algorithms focusing on NLP and CV applications
- Fine-tune and optimize models for improved performance across metrics
- Implement and deploy models into production systems when necessary
- Implement explainable AI algorithms to allow stakeholders to comprehend and trust model outputs
- Create informative and visually appealing data visualizations and dashboards to communicate findings
- Use tools like Grafana, or similar, to present data-driven insights to stakeholders
- Collaborate with cross-functional teams, including engineers, product managers, and business analysts
- Provide data-driven recommendations to support decision-making processes
- Ensure models and AI solutions adhere to ethical guidelines and responsible AI practices
- Monitor and mitigate biases in data and models to promote fairness and transparency
- Stay up-to-date with the latest advancements in NLP, CV, and responsible AI
- Apply new techniques and technologies to improve existing models and processes
