Management trainee Machine Learning

We are looking for a detail-oriented Data Scientist, Assistant Manager

to support Promo Model operations with high accuracy and timeliness for a Major US retailer. The role will be pivotal in model change requests, maintaining promo data, and driving actionable insights for Promo strategy through structured reporting and soft research. The ideal candidate is analytical, proficient in Tableau and SQL, and capable of independently executing margin and promotion impact analysis

Responsibilities

Under the direct supervision of internal Data Science managers, formulate solutions to problems related to membership acquisition, retention and engagement as well as digital and operations

Be able to independently frame business problems and decompose their constituent parts to determine proper data science solutioning

Build machine learning models and use applied statistics (supervised/unsupervised learning, lift modeling, linear/nonlinear programming, feature selection) to support the business

Enhance existing and build new technology solutions in support of business priorities

Use proper statistical techniques to provide ad hoc data science/EDA support when needed

Be a thought partner in the creation of our testing plans and provide next level insights related to the measurement of tests

Certify all testing/measurement (hypothesis testing, A/B testing, design of experiment, sample size/power calculation)

Communicate complex data science concepts/insights to non-technical audiences

Participate in agile work planning-projects will be selected from use cases across the enterprise

Drive continuous improvement by evaluating and implementing new data science methodologies, tools, and frameworks.

Qualifications we seek in you!

Minimum Qualifications

BSc in Computer Science, engineering (or related area), Statistics, Mathematics, or equivalent experience

Experience in developing machine learning models for retail use cases

Experience in crafting ad hoc data mining analysis for retail use cases

Experience in algorithms, data structures, and object-oriented programming

Experience on engineering and development collaboration tool such as Jira/Confluence/Git

Experience in mentoring and delegating work to junior analysts, involves providing essential business context, offering guidance on bug fixes, and conducting thorough reviews of their work

Implementation experience in building machine learning algorithms and applications, deploying and maintaining NLP models for retail use cases

Experience in time-series forecasting, clustering algorithms, and dimensionality reduction techniques

Strong programming skills in at least one object-oriented programming language (Python, PySpark, SQL, Java)

Experience with cluster-computing frameworks (e.g. Spark, Hadoop)

Expertise in configuring and managing large, complex data pipelines using AWS services (e.g., Glue, SageMaker, Lambda), with experience in GCP/Azure as a plus

Eager to learn new algorithms, new application areas and new tools

Experience with engineering and development collaboration tool such as GIT/Jira/Confluence

Experience using pipeline and automation tool including Jenkins and SageMaker

Extract actionable insights from complex datasets using data mining, statistics, and database techniques to measure/understand/improve member acquisition/engagement KPIs

Excellent communication and collaboration skills, working effectively across teams and stakeholders