Associate Data Scientist

Key Responsibilities:

Client & Delivery Ownership

• Lead end-to-end analytics engagements for clients, from problem definition and data exploration to modeling, insights, and recommendations.
• Partner with client stakeholders to understand business objectives and translate them into clear analytical approaches.
• Present insights, methodologies, and implications to non-technical and senior audiences, enabling confident decision-making.
• Manage multiple workstreams while ensuring quality, timelines, and impact.

Modeling & Analytics

• Develop and validate predictive and descriptive models across use cases such as:
• Media Mix Modeling (MMM)
• Multi-Touch Attribution (MTA)
• Forecasting, segmentation, and response/scoring models
• Drive feature engineering, model selection, and performance evaluation using real-world, imperfect data.
• Make informed trade-offs between accuracy, interpretability, and scalability based on client needs.
• Ensure models are well-documented, explainable, and fit for business use.

Collaboration & Leadership

• Collaborate closely with data engineering teams to ensure smooth model deployment, monitoring, and iteration.
• Mentor junior data scientists and analysts through code reviews, problem framing, and best practices.
• Contribute to reusable frameworks, accelerators, and best practices to improve delivery efficiency.

Required Skills:

• 4–6 years of experience in applied data science, analytics, or modeling roles—preferably in consulting, marketing analytics, or client-facing environments.
• Hands-on experience with Media Mix Modeling (MMM) and/or Multi-Touch Attribution (MTA).
• Strong foundation in machine learning, statistical modeling, and applied mathematics.
• Proficiency in Python and/or R, including experience with ML libraries (e.g., scikit-learn, XGBoost).
• Experience building forecasting, segmentation, and response/scoring models.
• Strong data preparation and feature engineering skills for large, real-world datasets.
• Excellent communication and stakeholder management skills, with the ability to explain complex analyses simply.

Desired Skills:

• Exposure to Bayesian modeling, causal inference, or optimization techniques.
• Familiarity with NLP or text-based analytics (e.g., topic modeling, embeddings).
• Awareness of LLM-based applications and applied AI use cases.
• Experience working with cloud platforms (AWS) or production ML workflows.
• Familiarity with digital marketing analytics, including paid media, SEO, and search-related data.
• Experience contributing to or leading analytics projects end-to-end.

Qualifications:

• Master’s or PhD in a quantitative field (Computer Science, Statistics, Applied Mathematics, Data Science, Economics, Engineering, or related).
• 4–6 years of experience in applied data science or analytics, preferably in consulting, marketing analytics, or client-facing roles.
• Demonstrated experience delivering models and insights into production or decision workflows, not just research prototypes.
• Experience working directly with clients or business stakeholders is strongly preferred.

The Company

• Founded in 2008, iQuanti is a data-driven digital marketing firm that uses analytics and proprietary models to deliver high-performance marketing programs. With more than 15 years of experience, iQuanti turns consumer insights into actionable growth strategies for some of the world’s largest brands. iQuanti’s proprietary ALPS tool leverages predictive modeling and algorithmic simulations to drive more effective client campaigns
• iQuanti has been recognized on the 2018 Inc 500/5000 list of fastest growing companies in the U.S. To explore more …visit our website www.iquanti.com

Interested folks can share resume at syeda.islam@iquanti.com