Senior Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

What you'll do...

Personalization team at Walmart is dedicated to the mission of knowing our customers better and making it frictionless and faster for them to get what they want while building a trusted partnership with Walmart. We help bring a seamless experience to our customers irrespective of how and where they engage with us – while shopping online or picking groceries at stores. We thrive to provide each customer with a journey tailored to their individual needs, preferences and routines. We operate at the intersection of huge Walmart assortment, millions of customers, thousands of stores and Walmart associates - a multi-layer multi-objective problem space which has a unique impact on Global customer base and powers assisted AI for our associates.

The Personalization team consists of big data geeks, application engineers, scientists and product visionaries all working together to design, prototype and build technology-driven products and experiences that will change the future landscape of e-commerce. We are focused on building an intelligent system that will enable 1:1 personalized customer experience, from finding the product to delivering it to the customer. We are building state-of-the-art probabilistic models and engineering platforms to serve our customer needs by leveraging cutting edge machine learning, deep learning, reinforcement learning, natural language processing, entity-relationship extraction and knowledge representation. This will span many markets, business models and form factors; therefore, we are looking for scientists and engineers who will bring not only an abundance of experiences in technologies, but an abundant curiosity to innovate.
We are looking for versatile Senior Data Scientist to focus on building complex, cutting edge, and scalable algorithms for our organization

• Data Strategy: Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function.
• Data Source Identification: Supports the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.
• Analytical Modeling: Selects the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models.
• Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data.
• Defines and finalizes features based on model responses and introduces new or revised features to enhance the analysis and outcomes. Identifies the dimensions of the experiment, finalizes the design, tests hypotheses, and conducts the experiment. Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business. Mentors and guides junior associates on basic modeling and analytics techniques to solve complex problems.
• Model Assessment & Validation: Identifies the model evaluation metrics. Applies best practice techniques for model testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and model ensembles.
• Model Deployment & Scaling: Supports efforts to ensure that analytical models and techniques used can be deployed into production. Supports evaluation of the analytical model. Supports the scalability and sustainability of analytical models.
• Code Development & Testing: Writes code to develop the required solution and application features by using the recommended programming language and leveraging business, technical, and data requirements. Test the code using the recommended testing approach.
• Data Visualization: Generates appropriate graphical representations of data and model outcomes. Understands customer requirements to design appropriate data representation for multiple data sets. Work with User Experience designers and User Interface engineers as required to build front end applications. Presents to and influences the team and business audience using the appropriate frameworks and conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance, and leverages rational arguments.
• Guide and mentor junior associates on story types, structures, and techniques based on context.
• Problem Formulation: Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.
• Applied Business Acumen: Provides recommendations to business stakeholders to solve complex business issues. Develops business cases for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Recommends new processes and ways of working.
• Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
• Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
• Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices.

Our Ideal Candidate Will Have:

• Experience with Java, Python, Pyspark, Scalding, Tensorflow, PyTorch or other related big data and machine learning technologies to design and develop robust high-performance and scalable applications
• Knowledge of data analysis methods and techniques (e.g., Dimensionality reduction, predictive modeling, clustering, text mining etc.) for feature engineering.
• Experience developing models with structured and unstructured data sets using advanced machine learning algorithms (Neural Networks, Regression Models, Gradient Boosting Algorithms).

Preferred Quals:

• Applied experience delivering to business customers using data science, machine learning, and optimization models. Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics. Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, pyspark, scikit learn, tensorflow, torch, scala)