Staff Data Scientist/Senior Data Responsibilities
- Serve as the technical lead on complex client engagements, owning analytical strategy, modeling approach, and solution quality.
- Partner closely with client stakeholders, analytics leads, and consulting teams to translate business questions into robust analytical solutions.
- Guide clients on measurement strategy, model interpretation, and decision implications, not just outputs.
- Influence analytical direction across multiple engagements through best practices, frameworks, and technical guidance.
- Design, develop, and validate advanced analytical models across use cases such as :
- Media Mix Modeling (MMM)
- Multi-Touch Attribution (MTA)
- Causal inference, forecasting, segmentation, and optimization
- Apply Bayesian and probabilistic modeling techniques (e.g., PyMC, Meridian) wherever appropriate to the business context.
- Lead feature engineering, model evaluation, and sensitivity analysis using real-world, imperfect data.
- Make informed trade-offs between model sophistication, interpretability, and actionability for client decision-making.
- Ensure models are client-ready, explainable, well-documented, and production-aware.
- Collaborate with data engineering teams to support deployment, monitoring, and iteration of models.
- Create reusable analytical components, accelerators, and methodologies to improve delivery efficiency and consistency.
- Review and elevate the quality of modeling work across the team through technical reviews and mentorship.
Required Skills
- 8- 12 years of experience in applied data science or advanced analytics, preferably in consulting, marketing analytics, or client-facing roles.
- Deep hands-on experience with Media Mix Modeling (MMM) and Multi-Touch Attribution (MTA), including Lightweight MMM and Meridian-based approaches.
- Strong expertise in Bayesian modeling and statistical inference (e.g., PyMC).
- Advanced proficiency in Python and/or R, with experience using ML libraries (scikit-learn, XGBoost; deep learning as applicable).
- Experience building models such as :
- Forecasting and response/scoring models
- Segmentation and optimization models
- Causal inference frameworks
- Strong ability to communicate complex analytical concepts clearly to senior, non-technical stakeholders.
- Proven track record of leading analytics projects end-to-end with real business impact.
Desired Skills
- Exposure to NLP or text analytics (topic modeling, embeddings).
- Familiarity with LLM-based applications and applied AI use cases.
- Experience with optimization, simulation, or reinforcement learning where relevant.
- Working knowledge of cloud platforms (AWS) and production ML workflows.
- Familiarity with digital marketing analytics, including paid media, SEO, and search-related modeling.
Qualifications
- Masters or PhD in a quantitative field (Computer Science, Statistics, Applied Mathematics, Data Science, Operations Research, Economics, Engineering).
- 8- 12 years of experience in applied data science/modeling, ideally with projects spanning MMM, MTA, predictive modeling, NLP, optimization, and business-focused analytics.
- Experience delivering models into production environments (not just research/prototyping).
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 worlds largest brands.
iQuantis 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.
(ref:hirist.tech)
