Data Science Manager

We are seeking a skilled and versatile Data Science Manager with AI familiarity to join our growing this role youll collaborate with practice leaders engineers and cross-functional stakeholders to solve complex business challenges using data science and AI-driven approaches. Youll work on end-to-end data science initiatives with opportunities to design and implement cutting-edge generative AI (GenAI) and LLM-powered solutions.

Key Responsibilities

Data Science & Analytics

• Partner with practice leaders and clients to understand business problems industry context data sources risks and constraints.

• Translate business needs into actionable data science solutions evaluating multiple approaches and clearly communicating trade-offs.

• Collaborate with stakeholders to align on methodology deliverables and project roadmaps.

• Leverage Machine Learning and Data Analysis to optimize marketing campaigns

• Conduct A/B tests to improve campaign performance measure campaign effectiveness and increase engagement and conversion rates. 

AI & Generative AI Collaboration

In addition to traditional data science responsibilities you will collaborate with AI and engineering teams to:

• Design and implement production-grade AI solutions leveraging LLMs transformers retrieval-augmented generation (RAG) agentic workflows and generative AI agents.

• Optimize prompt design workflows and pipelines for performance accuracy and cost-efficiency.

• Build multi-step stateful agentic systems that utilize external APIs/tools and support robust reasoning.

• Deploy GenAI models and pipelines in production (API batch or streaming) with a focus on scalability and reliability.

• Develop evaluation frameworks to monitor grounding factuality latency and cost.

• Implement safety and reliability measures such as prompt-injection protection content moderation loop prevention and tool-call limits.

• Work closely with Product Engineering and ML Ops to deliver robust high-quality AI capabilities end-to-end.

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• Develop and manage detailed project plans including milestones risks owners and contingency plans.

• Create and maintain efficient data pipelines using SQL Spark and cloud-based big data technologies within client architectures.

• Collect clean and integrate large datasets from internal and external sources to support functional business requirements.

• Build analytics tools that deliver insights across domains such as customer acquisition operations and performance metrics.

• Perform exploratory data analysis data mining and statistical modeling to uncover insights and inform strategic decisions.

• Train validate and tune predictive models using modern machine learning techniques and tools.

• Document model results in a clear client-ready format and support model deployment within client environments.

Qualifications :

Required Skills & Experience

• 5 years of hands-on experience in Data Science including model building and ML Ops
• Experience in email marketing and direct marketing 
• Experience managing people
• Proficiency in Python SQL and tools like Pandas Scikit-learn NLTK/spaCy and Spark
• Familiarity with digital marketing ecosystem (e.g. clickstream analytics) and recommendation systems 
• Experience deploying models via APIs or integrating them into batch processing pipelines
• Working knowledge of cloud data platforms (e.g. AWS S3 Redshift GCP Azure)
• Ability to manage data pipelines and ETL processes with a solid understanding of data engineering best practices
• Strong communication and collaboration skills including experience engaging directly with clients

Preferred Qualifications

• Exposure to ML Ops tools such as MLflow Kubeflow or SageMaker
• Experience working in Agile environments with cross-functional teams

Remote Work :

No

Employment Type :

Full-time