Senior Advisor, Data Science

Senior Advisor, Data Science

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. What’s more, we are in collaboration with leading academics, industry experts, and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.

What you’ll achieve:

As a Senior Advisor, you will lead initiatives in advanced analytics, machine learning, and data-driven decision-making. You will design scalable models, optimize algorithms, and collaborate across teams to deliver actionable insights. We are seeking a skilled data scientist with a proven track record of   building and maintaining Machine Learning models to join our Marketing forecasting team.

Join us to do the best work of your career and make a profound social impact as a  Senior Advisor  on our  Data Science team.

Responsibilities
You will:

- Gather and preprocess marketing data from various sources such cloud based/ on-premise databases ensuring data quality and consistency

- Develop and implement AI/ML/time series models to forecast sales demand and trend ensuring timely and accurate delivery of forecast.

- Experience in model orchestration using Airflow

- Work closely with marketing teams to understand data needs and provide actionable insights.

- Create visualizations to present data findings in a clear and actionable manner.

- Work with cross-functional teams, including go to market teams, data platform team to implement data-driven solutions

Qualifications
Take the first step towards your dream career

Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:
Essential Requirements

- Strong foundational understanding of regression analysis, including the ability to interpret coefficients meaningfully in both statistical and business contexts, Hands-on experience building marketing mix models, with a strong understanding of marketing performance measurement

- Ability to diagnose and address multicollinearity among correlated marketing variables and understand its impact on model reliability

- Understanding how to model interaction effects to capture how different factors amplify or diminish one another

- Awareness of biases that arise from unobserved factors, such as omitted variable bias, reverse causality, or simultaneity, and familiarity with strategies to mitigate them

- Understanding of good and bad control variables in regression modeling; ability to distinguish between confounders, mediators, colliders, or post-treatment variables. Ability to identify and avoid spurious regression, familiarity with causal inference techniques and proficiency in Python, and SQL

Desirable Requirements

- Bachelor's degree in Statistics, Econometrics, Data Science, Computer Science, or a related field; Master’s degree preferred Bachelor’s degree in Data Science, Computer Science, or related field; advanced degree a plus.

- Experience with machine learning algorithms and their application in marketing and maintaining version control of artifacts (GitHub, GitLab)