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

Key Skills

Skills highlighted with ‘‘ are preferred keyskills