- Understand market trends and our clients' pain points, to lead, along with other Lab leaders, the Lab's R&D road map for next 3-5 years to addresses industry needs
- Follow new technologies in AI and Machine Learning, and guide the R&D efforts to apply the latest technology to address our client's challenges.
- Lead the development of impactful analytical solutions with Return on investment related to Identity management, fraud detection, risk management, and marketing optimization.
- Solve complex challenges by developing impactful algorithms
- Craft advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources.
- Lead efforts to improve the Lab's data management, data processing, knowledge discovery and modeling process
- Coach junior team members of the Lab
- Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques.
- Improve data manipulation and retrieval through the design of efficient data structures and storage solutions.
- Innovate with tools designed for data processing and information retrieval.
- Dissect and document vast datasets, analyzing them to highlight patterns and insights.
- Ensure model excellence by validating performance scores and analyzing Return on investment and benefits.
- Articulate model processes and outcomes, documenting and presenting findings and performance metrics
- #LI-Remote
- Ph.D degree in Machine Learning, Data Science, AI, Computer Science, or a related quantitative field.
- More than 10 years of experience in AI, data science, and predictive modeling
- Track record in leading development of impactful analytical solutions with Return on investment for fraud detection, risk management, or marketing optimization.
- Experienced in leading sizable teams to develop AI driven analytical solutions
- Proficiency in multiple programming languages, including Python, Java, C++, and C
- Experience developing analytical solutions using deep learning (CNN, RNN, LSTM, attention models), machine learning methodologies (SVM, GLM, boosting, random forest, etc.), graph models, and reinforcement learning.
- Experience with open-source tools for deep learning and machine learning technology such as pytorch, Keras, tensorflow, scikit-learn, pandas
- Experience with large data analysis using Spark (pySpark preferred)
- Experience with LLMs and the relevant tools in the Generative AI domain.
- Experience developing advanced language models
- Experience in developing and applying Generative AI based technology
- Experience with Hadoop and NoSQL related technologies such as Map Reduce, Hive, HBase, mongoDB, Cassandra.
- Experience with GPU programming
- Great compensation package and bonus plan
- Core benefits including medical, dental, vision, and matching 401K
- Flexible work environment, ability to work remote, hybrid or in-office
- Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
- Explore all our exciting benefits here:
Apply for the job now! Apply Now