Principal Data Scientist

Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs). Are you able to naturally and quickly expand your core data science skills as an individual contributor and also develop, mentor and train your junior peers in the Data Science area.  ServiceLink, the unrivaled mortgage industry leader, is in search of a Principal Data Scientist to drive the delivery of business results through data-driven technologies and processes, serving as a strategic advisor and problem solver to our dynamic business.  

The ideal candidate will have experience in identifying future technology trends, their risks, and opportunities, implementing the necessary and sufficient data-driven tools to address them in alignment with business needs and infrastructure requirements. Additionally, they will be fluent in analyzing large, complex, multi-dimensional datasets with a variety of tools and statistical environments, encompassing the end-to-end data lifecycle: data gathering, governance, analysis, modeling, presentation, and deployment, preferably abiding by consolidated frameworks such as CRISP-DM and ML-OPS. Proficiency in implementing machine learning and advanced statistics algorithms and can interface with software engineering to deploy data-driven solutions at scale is a must, along with the ability to clearly determine and communicate the reach as well as the limitations of data-scientific approaches within complex business environments and uncertain scenarios. Experience developing publications in reputed scientific journals (impact factor 10 or higher) to establish the Company brand in the Data Science field, while protecting Company IP is also desired. This is an exciting time to join ServiceLink, where those at the forefront of technology excel in our entrepreneurship culture focused on empowerment and innovation.

A DAY IN THE LIFE

In this role, you will…

· Understand business requirements and recommend/formulate/implement the suitable data-scientific approach(es) to address them.

· Determine and fulfil sampling needs for Deep Learning and Large Language Models.

· Master current and future states of Microsoft Azure NLP APIs.

· Conceive and execute the entire development plan to build, optimize and deploy Deep Learning and Large Language Models.

· Quickly and frequently update on challenges to maximize the performance of Deep Learning and Large Language Models, as well as devise and implement the corresponding solutions.

· Build and maintain automated tools to measure and display model performance throughout their development lifecycle.

· Interface with Data Engineering and Product Development teams for the deployment of high-performing and maintainable Deep Learning and Large Language Models.

WHO YOU ARE

You possess …

· Graduate degree with 10+ years of experience in strong quantitative field, such as Computer Science or Engineering.

· Comfortable in navigating both classical statistics and recent machine learning methods, separately or in combination, aligned with business and infrastructure guidelines.

· Able to communicate and share complex quantitative knowledge with broad audiences.

· Effective in fast paced environment.
· Collaborative/enjoys working in teams.
· Self-starter/motivator, can provide guidance and build credibility based on results.

· Ability to explain and make decisions based on technical/cost/risk trade-offs.
· Experience in software or applications engineering and/or technical operations.

·          Actively interface with business stakeholders to identify and address risks/opportunities by way of data-scientific approaches.

·          Propose and implement concrete solutions on how data science can best serve diverse and complex business needs.

·          Work closely with other functional teams to integrate ideas, innovations, intellectual property, and algorithms into production systems, rapidly and efficiently evolving from PoC into production.

·          Develop publications in reputed (impact factor 10 or higher) journals to establish company brand on data science, while protecting IP and critical business information.

·          Support project execution and product development as required, providing both technical guidance to peers and hands-on work.

·          Develop/maintain global and specific metrics, creating the ability to generalize Deep Learning and Large Language Models into various geographic locations, timeframes and document types.

·          Collaborate with infrastructure/architecture areas to ensure cost-effective and secure capabilities for current and future data-scientific solutions.

·          Continuously measure the effectiveness of existing data-scientific solutions and work towards their improvement.

·          Being able to work in a fast-paced and multidisciplinary environment, adapting to changes in business and resources conditions.

·          All other duties as assigned.

·         Graduate degree required, industry experience is a plus.

·         A strong drive to acquire and share new technologies and techniques in all phases of data science, enabling peers to the same as applicable.

·         Ability to translate enhanced methods to code (Python, R, Azure NLP APIs).

·         Experience in software or applications engineering and/or technical operations.

·         Work experience building data-driven applications using/integrating/improving any of the following:

                      o   Data cleansing, manipulating datasets within databases and programing languages (R, Python).

                      o   Developing various Machine Learning, Deep Learning and Large Language Models

                      o   Fluency in cloud environments and Microsoft Azure.

·         Ability to shape current data scientific practices into future trends, with both gradual and disruptive innovation approaches.

·         Collaborative/enjoys working in teams.

·         Self-starter/motivator.

·         Creative and effective problem-solving skills.

·         Ability to work on/perform multiple tasks concurrently.

·         Excellent verbal and written communication skills.