QMMX – Data Scientist – Market Mix Modelling

Job description • Data Scientist - Market Mix Modelling (MMM/MMX) role at Quation Solutions Pvt Ltd:Welcome to Quation, where data transforms into the currency of informed decisions. We are more than a data analytics company; we are the architects of your data-driven success. Our commitment to precision, innovation, and industry transformation sets us apart. At Quation, we embody the essence of “Powering Data, Empowering Decisions.” We are driven by the belief that data, when harnessed intelligently, has the power to revolutionize industries, driving growth and efficiency. Join us in revolutionizing the world of data analytics, AI, and ML.Please visit https://quation.in/ for detailed information on Quation Solutions Pvt Ltd.Job Title: Data Scientist - Market Mix Modelling (MMM/MMX)Responsibilities: • Lead the design and development of advanced Market Mix Models (MMM) using Bayesian frameworks. • Build efficient and scalable probabilistic modelling tools to support MMM. • Integrate econometric principles and advanced statistical techniques (e.g., hierarchical modelling, time-series analysis, causal inference) to improve MMM accuracy. • Explore emerging methodologies like multi-touch attribution (MTA) and incrementality testing to complement MMM. • Design and deploy automated MMM pipelines using Python and cloud platforms (AWS, Azure, or GCP). (Good to Have) • Handle the technical aspects of MMM independently, managing multiple iterations of the project (e.g., Adstock application, saturation curve optimization). • Develop logical code to convert the theoretical aspects of MMM into actionable business solutions. • Provide mathematical explanations for optimization processes, focusing on objective functions and the logical building of models. • Collaborate closely with cross-functional teams to translate business requirements into effective MMM solutions.Basic Qualifications: • 4-6 years of experience in Market Mix Modelling or marketing analytics, with a proven track record of delivering high-impact projects. • Advanced degree (master’s or Ph.D.) in Statistics, Data Science, Economics, Computer Science, or a related field. • Immediate joiners are preferred or candidates with a maximum 15-day notice period. Preferred Qualifications: • Strong experience with Bayesian Modelling and probabilistic programming. • Expertise in tools such as Google Meridian/LightWeightMMM, Uber Orbit, Bambi, and custom Bayesian implementations. • Deep understanding of econometric modeling, time-series analysis, causal inference, and hierarchical/multi-level modelling. • In-depth knowledge of marketing analytics, including media attribution, channel optimization, and key marketing KPIs. • Familiarity with cloud platforms (e.g., AWS – S3, Lambda, SageMaker, Azure, or GCP) for scalable deployments is a plus. Suggested Skills: • Programming & Libraries: Expert-level Python skills (e.g., PyMC3/PyMC4, NumPy, pandas, SciPy, Matplotlib, Plotly, Seaborn). • Bayesian Modelling: Deep expertise in probabilistic programming and Bayesian frameworks; experience with libraries like Stan, TensorFlow Probability, is a plus. • MMM Tools: Proficient in tools such as Google Meridian/LightWeightMMM, Uber Orbit, Bambi, and custom Bayesian implementations. • Econometrics & Statistics: Strong grasp of econometric modeling, time-series analysis, causal inference, and hierarchical/multi-level modelling. • Marketing Analytics: Advanced knowledge of media attribution, channel optimization, and marketing KPIs. • Cloud Platforms (Good to Have): Hands-on experience with AWS (S3, Lambda, SageMaker), Azure, or GCP for scalable deployments. Location : Bangalore , Mumbai , Delhi NCR , Hyderabad, Chennai If interested or have relevant profiles: Please share your resumes at hiring@quation.in • CTC: As per market standards. Notice Period: Immediate joiners to 30 days’ notice period candidates will be preferred. We look forward to having you join us and contributing to our vision of transforming data into powerful business in • Apply for this Job with this Google form Link: https://forms.gle/K7ka4BpeBoc3oYWz9