Role Description:

As a Lead Data Scientist, you will be a key player in driving the success of our data science initiatives, leading the execution of impactful projects, and mentoring a team of talented data scientists. You will act as a bridge between technical expertise and cross-functional teams in Sales, Marketing, Customer Success, and Product Development to identify opportunities for AI and ML to solve complex problems and drive strategic growth. This role requires a blend of technical proficiency, leadership skills, and a strong understanding of business goals.

Responsibilities:

Lead and mentor a team of data scientists, providing technical guidance, fostering professional development, and promoting a collaborative work environment.

Collaborate with stakeholders across departments to understand business needs, translate them into data-driven solutions, and communicate technical concepts effectively to non-technical audiences.

Lead the design, development, and implementation of innovative data science solutions, including machine learning models, statistical analyses, and predictive algorithms.

Develop and maintain robust data pipelines for data acquisition, cleaning, transformation, and feature engineering, ensuring data quality and efficiency.

Train, validate, and deploy ML models using various algorithms, including regression, classification, clustering, time series forecasting, and reinforcement learning.

Evaluate model performance, identify opportunities for improvement, and implement optimization strategies.

Propose and implement best practices and standards for data science development, ensuring consistency, efficiency, and quality across projects.

Lead the execution of complex projects, guiding the team through all stages of the data science lifecycle.

Identify new opportunities for leveraging data science to gain a competitive advantage and drive business growth.

Contribute to the development and execution of the data science roadmap, aligning initiatives with overall business objectives and prioritizing projects for maximum impact.

Stay up to date on the latest trends and advancements in machine learning, data science, and related technologies.

Champion the adoption of data science best practices across the organization, fostering a data-driven culture.

Qualifications:

Master's degree in Statistics, Computer Science, Data Science, or a related field.

7+ years of experience in a data science role, with a proven record of accomplishment developing and deploying successful machine learning solutions.

Strong proficiency in Python, R, or other statistical programming languages.

Expertise in machine learning algorithms, including deep learning, ensemble methods, and time series analysis.

Experience with specific ML frameworks like TensorFlow, PyTorch, or scikit-learn.

Familiarity with cloud platforms such as AWS, Azure, or GCP, and experience with cloud services specifically tailored for ML development and deployment (Vertex AI, BigQuery, SageMaker, Redshift, Azure ML Studio).

Experience working with relational databases (e.g., MySQL, PostgreSQL, SQL Server) and NoSQL databases (e.g., MongoDB, Cassandra), including data modeling, query optimization, and data integration.

Strong proficiency in SQL for data querying, manipulation, and analysis, including experience with advanced SQL features like window functions and CTEs.

Experience using Python libraries like Pandas, NumPy, and Dask for data cleaning, transformation, and feature engineering.

Strong understanding of statistical concepts, hypothesis testing, and data analysis.

Experience working in an Agile environment following Scrum methodology.

Excellent communication and presentation skills, with the ability to clearly convey technical concepts to non-technical audiences.

Ability to work independently and as part of a team, contributing to a collaborative and positive work environment.

Strong problem-solving skills and a passion for data-driven decision making.

Experience working in a SaaS environment is a plus.

Demonstrated leadership skills, including the ability to mentor and guide other data scientists.

Proven ability to identify opportunities for AI/ML applications and communicate their potential value to business stakeholders.

Bonus Points:

Experience with Natural Language Processing (NLP), Large Language Models (LLMs), Natural Language Understanding (NLU), and Retrieval Augmented Generation (RAG) techniques, or other Generative AI technologies.

Where we're going

UKG is on the cusp of something truly special. Worldwide, we already hold the #1 market share position for workforce management and the #2 position for human capital management. Tens of millions of frontline workers start and end their days with our software, with billions of shifts managed annually through UKG solutions today. Yet it's our AI-powered product portfolio designed to support customers of all sizes, industries, and geographies that will propel us into an even brighter tomorrow!

UKG is proud to be an equal opportunity employer and is committed to promoting diversity and inclusion in the workplace, including the recruitment process.

Disability Accommodation

For individuals with disabilities that need additional assistance at any point in the application and interview process, please email UKGCareers@ukg.com