I&F Decision Sci Practitioner Specialist

Skill required: Delivery - Digital Marketing Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years What would you do? Data & AIIn digital marketing analytics, you will be involved in processes and technologies that enable marketers to effectively evaluate the success and value of their digital marketing initiatives, identify trends and patterns over time and make data driven decisions. What are we looking for? Data Science Proficiency in Data Modeling, Experimental Design/Analysis, Marketing and/or Business Analytics. Knowledge of Data Science and Machine Learning concepts and algorithms. Experienced with programming languages and Data Science scripting (in Python / R / Scala / Julia) Experience with Cloud Technologies Experience in implementing ethical practices into data science. Negotiation skills Problem-solving skills Adaptable and flexible Results orientation Prioritization of workload Roles and Responsibilities: Utilize advanced statistical and machine learning techniques to address complex business problems Possess the ability to conduct exploratory data analysis and present findings in ways that are meaningful to stakeholders Develop, refine, and implement models that enhance decision-making processes. Perform comprehensive preprocessing of both structured and unstructured data to ensure its quality and relevance Undertake data collection, analysis, and interpretation to extract meaningful insights. Analyze vast datasets to identify trends, patterns, and correlations that contribute to informed decision-making Build, refine, and deploy predictive models and machine-learning algorithms that align with business objectives Collaborate closely with engineering and marketing teams to understand their requirements and integrate data-driven solutions into their workflows Conduct ad-hoc analyses to provide timely and relevant insights, along with actionable recommendations to address pressing business questions Develop and implement machine learning solutions, including audience segmentation, marketing engagement level evaluation, and prioritization of sales engagement with accounts Manage the end-to-end lifecycle of machine learning models, including training, testing, deployment, and continuous improvement Effectively communicate complex findings and insights to both technical and non-technical stakeholders Document methodologies, data sources, and models to ensure transparency and reproducibility Qualifications Any Graduation