Staff Data Scientist - Machine Learning

Staff Data Scientist/Senior Data Scientist.

Key Responsibilities :

- 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 :

1. Media Mix Modeling (MMM)

2. Multi-Touch Attribution (MTA)

3. 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 :

- 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 :

1. Forecasting and response/scoring models

2. Segmentation and optimization models

3. 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 :

- 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 :

- 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 :

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.