Senior Data Scientist

  • Sunnyvale, CA
  • Posted 10 days ago | Updated 10 hours ago

Overview

On Site
USD 144,075.00 - 234,000.00 per year
Full Time

Skills

Tableau
Microsoft Power BI
Visualization
User Experience
UI
Communication
IBM Rational
Mentorship
Marketing
Sales
Business Systems
Human Resources
Business Cases
Return On Investment
Cost Reduction
Business Strategy
Big Data
Use Cases
Natural Language Processing
Solaris Volume Manager
Support Vector Machine
Calculus
Statistical Models
Microsoft Excel
Programming Languages
R
Numerical Analysis
Optimization
Linear Programming
Modeling
Analytical Skill
Data Analysis
Dimensional Modeling
Cluster Analysis
Data Science
Computer Science
Statistics
Analytics
Apache Spark
Deep Learning
XGBoost
k-nearest neighbors
SQL
Writing
Unstructured Data
Python
Management
Machine Learning (ML)
Testing
Data Visualization
matplotlib
Algorithms
Distributed Computing
Cloud Computing
Data Storage
Finance
Life Insurance
Military

Job Details

What you'll do...

Position: Senior Data Scientist

Job Location: 1375 Crossman Avenue, Sunnyvale, CA 94089

Duties: Perform data visualizations: visualization guidelines and best practices for complex data types; Multiple data visualization tools (Python, R libraries, Ggplot, Matplotlib, Ploty, Tableau, PowerBI etc.); Advanced visualization techniques/tools; Multiple story plots and structures (OABCDE); Communication and influencing technique; Emotional intelligence. Generate appropriate graphical representations of data and model outcomes. Understand 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. Present to and influence the team and business audience using the appropriate data visualization 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. Understanding Business Context: Requires knowledge of Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with a projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serve as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Leverage knowledge of analytics, big data analytics, and automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. Translate and co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide a solution for the problem. Share use cases and gives examples to demonstrate how the method would solve the business problem. Leverage knowledge of feature relevance and selection; exploratory data analysis methods and techniques; Advanced statistical methods and best-practice advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.); Multivariate calculus; Statistical models behind standard ML models; Advanced excel techniques and Programming languages like R/Python; Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent); Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.). Select the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models. Conduct exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data. Define and finalize features based on model responses and introduces new or revised features to enhance the analysis and outcomes. Identify the dimensions of the experiment, finalize the design, test hypotheses, and conduct the experiment. Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business.

Minimum education and experience required: Master's degree or the equivalent in Data, Science, Computer Science, Statistics, or related field and 1 year of experience in analytics or a related field; OR Bachelor's degree or the equivalent in Data, Science, Computer Science, Statistics, or related field and 3 years of experience in analytics or a related field.

Skills required: Must have experience with: Writing production level code in Python and/or Spark-ML; Developing models and machine learning and deep learning algorithms: XGBoost, random forest, KNN, deep neural networks; SQL development: writing queries, transforming data, and mining structured and unstructured data; Processing, cleaning, validating, and found insights from dataset using Python; Perform feature engineering, outlier handling, encoding, scaling for numerical, categorical, text and time-based features; Track and manage machine learning experiments for reproducibility, versioning and deployment using technologies: MLflow; Optimize and fine tune pretrained and custom models for better performance; Design experiments and perform statistical significance testing to validate hypotheses and improve models; Data visualization proficiency using tools: Matplotlib, Seaborn, Streamlit; Parallelize and optimize algorithms for distributed computing frameworks to ensure efficient utilization of resources; Cloud platforms for data storage, processing, and analysis. Employer will accept any amount of experience with the required skills.

Salary Range: $144,075/year to $234,000/year. Additional compensation includes annual or quarterly performance incentives. Additional compensation for certain positions may also include: Regional Pay Zone (RPZ) (based on location) and Stock equity incentives.

Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.

Wal-Mart is an Equal Opportunity Employer.

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