Data Science Manager

Jobtailor; Hoboken (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor in Hoboken, NJ seeks a Data Science Leader to own and shape the roadmap for our Customer Development products, aligning analytics with commercial priorities and business outcomes.

You will lead the design, development, and deployment of diagnostic, predictive, and prescriptive analytics at scale on Azure/Databricks, mentor a team of data scientists, and partner with product, engineering, and business stakeholders to drive adoption and data-driven decision making.

Qualifications

• Degree qualified in a technical discipline (Data Science, CS, Engineering, Mathematics, Statistics, Econometrics).
• Proven experience leading data science teams on complex analytics in a commercial or product environment.
• Strong modelling background: econometrics, time series, simulations, optimization; ML at scale.
• Experience with generative/agentic AI is a strong advantage.
• Proficiency with Python, Spark; Databricks and Azure for productionised solutions.

Responsibilities

• Own and shape the data science roadmap for the CD portfolio, aligned to commercial priorities and outcomes.
• Lead design, development, and deployment of diagnostic, predictive, prescriptive analytics at scale.
• Set modelling and analytical standards across the team across multiple techniques.
• Industrialise solutions with cloud platforms and MLOps practices.
• Coach and develop a team of data scientists; drive growth and delivery discipline.
• Collaborate with Product, Engineering, and Business to define problems and drive adoption.
• Translate analytics into clear, actionable insights for senior stakeholders.
• Foster agile ways of working and fast, iterative delivery.

Skills

Data science team leadership

Machine learning solution design

Econometric modeling

Time series forecasting

Communication

Education

Degree in Data Science / CS / Engineering

Tools

Azure

Databricks

Spark

Python

Job description

• Own and shape the data science roadmap for products within our Customer Development (CD) portfolio, aligned to commercial priorities and business outcomes.
• Lead the design, development, and deployment of diagnostic, predictive, and prescriptive analytics solutions, ensuring robustness, scalability, and interpretability.
• Set modelling and analytical standards across the team, covering classical statistical methods, machine learning, and emerging Generative and Agentic AI capabilities.
• Ensure solutions are industrialised and production-ready, leveraging cloud platforms (Azure, Databricks) and aligned with MLOps best practices.
• Lead, coach, and develop a team of data scientists, supporting both technical growth and career progression.
• Foster a culture of high ownership, continuous improvement, and learning, encouraging experimentation while maintaining delivery discipline.
• Provide technical guidance and review, acting as a mentor and escalation point for complex analytical challenges.
• Partner closely with Product, Engineering, and Business stakeholders to shape problem definitions, prioritise initiatives, and drive adoption of data science solutions.
• Translate complex analytics into clear, actionable insights for senior stakeholders, supporting data-driven decision-making.
• Champion agile ways of working, enabling fast-paced experimentation and iterative delivery.

Requirements

• Degree qualified in a relevant technical discipline (Data Science, Computer Science, Engineering, Mathematics, Statistics, Econometrics, or similar)
• Proven experience leading data science teams working on complex analytics initiatives in a commercial or product-driven environment
• Strong background in data science modelling, with deep expertise in several of the following:
• o Econometric modelling (Regression, Bayesian approaches) especially in the context of pricing and promotions in the CPG/Retail space
• o Time series forecasting
• o Simulation and optimisation tools
• Experience designing and industrialising machine learning solutions at scale; exposure to agent-based AI systems is a strong advantage.
• Advanced proficiency in Python, Spark, and modern analytics stacks; hands‑on experience with Databricks and Azure.

Core Competencies

Demonstrates expertise in leading data science teams and developing robust analytics solutions, with a strong focus on machine learning, econometric modeling, and cloud platforms. Capable of translating complex data insights into actionable strategies while fostering a culture of continuous improvement and agile methodologies.

Highest-signal resume keywords

• Data Science Team Leadership
• Machine Learning Solution Design
• Econometric Modeling Expertise
• Advanced Python Proficiency
• Cloud Platform Experience (Azure, Databricks)

ATS Optimization Keywords

Hard Skills

• Data Science Modeling
• Econometric Modeling
• Time Series Forecasting
• Simulation and Optimization Tools
• Predictive Analytics
• Prescriptive Analytics
• Statistical Methods
• Generative AI
• Agentic AI
• MLOps Best Practices

Soft Skills

• Coaching and Mentoring
• Collaboration
• Problem-Solving
• Communication
• Continuous Improvement

Industry Keywords

• Customer Development
• Commercial Priorities
• Data-Driven Decision-Making
• Agile Methodologies
• CPG/Retail

Tools & Technologies

• Azure
• Databricks
• Spark
• Modern Analytics Stacks