Data Scientist – ML & Data Engineering

Centrical provides an employee-centric success platform that holistically navigates employees, turn-by-turn, to success. Using actionable KPIs, deep gamification, personalized microlearning, collaboration tools, and augmented coaching, Our Story

Centrical grew out of the business intelligence (BI) software segment. BI let managers know how employees were doing, but it typically did not convey how to turn manager-led performance insights into employee performance actions.

Since employees were the ones doing the work, Centrical’s vision was to place them at the center of the process. To share with them insights about their work, to help them improve, be more focused, get better at what they do, as well as make it fun. Along with that, Centrical empowers managers to enable their team members to be more successful with AI-powered, closed-loop coaching that triggers personalized activities that impact individual employee performance and real-time performance visibility. That makes for better coaches and better-performing employees.

Centrical, founded in 2013, is convinced that employees are the center of business success. We operate from offices in New York City and Israel. And are proud to have an expanding list of enterprise businesses as customers, including Microsoft, Teleperformance, Synchrony Financial, Webhelp, and Swiss Life, among others.

The Data Scientist will Build advanced analytics workflows, robust data pipelines and analytic use cases.

Responsibilities

Analyze and interpret data from multiple sources to identify trends, anomalies, and opportunities for improvement.

Apply statistical modeling, machine learning, and predictive analytics to generate deeper business insights.

Partner with business units across the organization to gather requirements and deliver actionable, data-driven solutions.

Build, test, and maintain analytical models using Python (pandas, NumPy, scikit-learn, etc.).

Design and maintain advanced analytics workflows for leveraging platforms such as Python, Amazon Redshift, QuickSuite and more.

Translate complex analyses into clear, actionable insights for both technical and non-technical stakeholders.

Collaborate with Product, BI, and Data Science teams to ensure alignment of analytics solutions with business goals.

Requirements

3+ years of experience in analytics, data science, or other quantitative roles; prior experience with SaaS an advantage.

Proficiency in Python for data analysis, including libraries such as pandas, NumPy, scikit-learn, matplotlib, seaborn, and other relevant toolkits.

Proficiency in SQL.

Experience with statistical analysis and predictive modeling.

Familiarity with Jupyter Notebooks or similar environments for analysis and reporting.

Demonstrated curiosity and willingness to discover, learn, and leverage new AI tools and technologies to enhance efficiency, speed, and overall job performance.

Deep analytical and problem-solving skills, with a keen eye for detail.

Able to excel in a rapidly changing, hyper-growth, start-up environment, as an entrepreneurial, self-starter, and highly collaborative team member.

Strong written and verbal communication skills, with the ability to distill complex analytical concepts into actionable insights and communicate impact to non-technical audiences.

BA or BS in a quantitative field (e.g., Data Science, Statistics, Computer Science, Engineering, Mathematics, Economics).

Fluent English speaker

Preferred Qualifications

MSc or PhD in a quantitative field.

Experience with AWS.

Experience and knowledge in agentic workflows.

Experience with Amazon Redshift.

Experience with Scrum and Jira.

Experience with Jenkins.

Experience with DBT

Experience deploying data solutions and integrating analytics into business workflows.

To apply please send your CV to [email protected]