Data Science

Key Skills

Java Programming, Design of Experiment, Python Programming, SQL, Apache Kafka, ETL/ELT technologies, Keras software library, TensorFlow, spaCy, Natural Language Toolkit - NLTK, R Programming, SPARK Programming

Job Description

We are transforming Marketing at Dell. Come join Dell's Customer Engagement Platform. 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. We are looking for a passionate data scientist to develop a robust, scalable data model and optimize the consumption of data sources we require to generate unique insights about our systems. You will be solving some of the hardest problems for business leveraging ML/AI. Most of our use cases start with 10 million+ rows of data. The models and solutions you deliver will be the essential ingredient we use to supply our customers & sales with relevant product recommendations and creative breakthroughs to our business.

What are our goals in Marketing?

• Drive perception.
• Drive demand.
• Grow the buyer base.
• Build the best content.

What You’ll Achieve

As a Data Scientist Advisor, you should have extensive experience in analyzing and building models against extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build models and simulations that answer those questions. We expect you to be familiar with most of the standard methods: linear regression, logistic regression, regularized regressions, nearest neighbors, k-means, DB scan, collaborative filtering, decision trees, random forests, extreme gradient boosting, support vector machines, neural networks and deep learning – including deep neural networks and deep belief networks. However, it is also important to be creative in applying/implementing new methods or combinations of those to our data. You will be applying, but also developing/improving, supervised and unsupervised algorithms.

You will have the opportunity to demonstrate and develop your analytical and technical skills with challenging projects and work with our experienced data scientists and big data engineers. Expect to expand your skills in Python / R, the Hadoop ecosystem including Spark (Scala / PySpark / SparklyR) & Hive, relational databases, and applying machine learning techniques to large datasets.

We offer you a fast-paced work environment in a diverse team with exposure to Dell teams across the globe. You will be part of a dynamic, collaborative and cross-functional team focused on making significant business impacts.

You will:

• Lead discussions to frame problem statements, develop hypotheses, design data frames, recommend modeling approaches, measure success & testing criteria
• Establish scalable, efficient, automated processes for large scale feature engineering, model development, model validation and production
• Communicate with product teams and leadership and turn hard and abstract into simple and approachable

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

You have professional experience. 3+ years of experience in predictive modeling and analysis, designing and implementing solutions to drive business outcomes.

• Proficiency in Python or R especially on data wrangling, analysis, and modeling.
• Expertise in experiment design and methods, from A/B tests to quasi-experiments.
• Excellent problem solving, analytic skills, and written and oral English communication skills.

Education (Master’s degree or higher) in Statistics, Computer Science, Mathematics, or a related technical field, or equivalent practical experience. Experience with data engineering and data science technologies, such as concurrent data processing (e.g., Spark), natural language processing (e.g., NLTK, spaCy), deep learning (Keras, Tensorflow). Knowledge on data streaming (e.g., Kafka), ETL processes.

In addition to the above, it’s a plus if you have:

Experience deploying large scale data / machine learning pipeline solutions using Spark, Docker, Kubernetes, CI/CD, MLFlow, etc. Software engineering experience particularly related to productionizing machine learning models and scaling them in low-latency settings. Experience with Apache Spark in particular MlLib (incl. Scala, PySpark and/or SparklyR) Have deployed models in production or know how it is done. Experience with Kubeflow or other docker/container-based solutions. Experience with Pytorch or Tensor flow are big plus. Experience with Object Oriented Design / Object Oriented Programming. Experience with any monitoring tools such Dynatrace, NewRelic, Splunk. Experience container-based technologies (e.g., docker, Kubernetes).

Salary starting from: 2500 EUR gross monthly