Principal Data Scientist

**Job Description**:
**Job ID**:

- PRINC008707**Employment Type**:

- Regular**Work Style**:

- on-site**Location**:

- Noida,UP,India**Role**:

- Principal Data ScientistCompany Overview

With 80,000 customers across 150 countries, UKG is the largest U.S.based private software company in the world. And we’re only getting started. Ready to bring your bold ideas and collaborative mindset to an organization that still has so much more to build and achieve? Read on.

At UKG, you get more than just a job. You get to work with purpose. Our team of U Krewers are on a mission to inspire every organization to become a great place to work through our award-winning HR technology built for all.

Here, we know that you’re more than your work. That’s why our benefits help you thrive personally and professionally, from wellness programs and tuition reimbursement to U Choose — a customizable expense reimbursement program that can be used for more than 200+ needs that best suit you and your family, from student loan repayment, to childcare, to pet insurance. Our inclusive culture, active and engaged employee resource groups, and caring leaders value every voice and support you in doing the best work of your career. If you’re passionate about our purpose — people —then we can’t wait to support whatever gives you purpose. We’re united by purpose, inspired by you.

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