Note: The job is a remote job and is open to candidates in USA. Nestlé Health Science is dedicated to merging nutrition, science, and wellness to empower healthier lives. They are seeking a Senior Data Scientist to develop and deploy advanced analytics and AI solutions that drive business impact within the Consumer Insights and Analytics team.
Responsibilities
- Advanced Analytics & Insights: Develop and implement data science solutions, leveraging advanced analytics to drive data-driven decision-making, optimize business performance, and support Consumer Insights & Analytics priorities
- Data Analysis & Modeling: Analyze large and complex datasets to identify patterns, build statistical and machine learning models, and solve critical business problems using big data technologies like Databricks, Azure ML, and Apache Spark, as well as strong data visualization for structured storytelling to drive impactful business decisions
- Developing Advanced Models: Design deep learning and natural language processing models to analyze complex data across business processes
- Model Monitoring & Performance Optimization: Continuously track, evaluate, and refine deployed models to maintain accuracy and relevance over time
- AI Research & Evaluation: Research, test, and evaluate AI technologies to ensure the best tools and platforms are used for achieving business objectives
- Enhancing Analytical Capabilities: Integrate the latest data science innovations into product solutions, enhancing data, analytical, and automation capabilities
- Cross-Functional Collaboration: Work closely with cross-functional teams and stakeholders to provide expertise across omnichannel analytical projects and ensure alignment with business goals
- Tool Development & Maintenance: Build, maintain, and improve analytics tools to enhance capabilities and accelerate speed to value
Skills
- Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Mathematics, Physics, Operations Research, Statistics, or a related field
- 5+ years of experience as a Data Scientist, Machine Learning Engineer, or Applied Scientist, specializing in computer vision, natural language processing, or data synthesis
- Experience developing and deploying advanced analytical models and algorithms
- Experience applying machine learning techniques, including Regression, Clustering, Probability Networks, Artificial Intelligence (AI), and Deep Learning
- Hands-on programming experience in Python and R, leveraging advanced cognitive and machine learning methods to solve business challenges
- Experience working with relational database and cloud computing technologies such as Databricks, Snowflake, AWS, Azure ML and AMC, Big Query
- Experience in transforming raw data into meaningful features for machine learning models
- Expertise in handling missing data, scaling, encoding categorical variables, and dimensionality reduction techniques
- Hands on experience in designing and analyzing A/B tests and other experimental methodologies
- Hands on experience in causal inference techniques to measure the impact of business decisions
- Experience visualizing and presenting data-driven insights using Power BI and Tableau
- Experience in developing recommendation engines for applications such as sales, customer targeting, or supply chain optimization
- Experience in building and implementing optimization models to enhance decision-making processes
- Familiarity with agile methodologies and rapid prototyping in data science projects
- Strong knowledge of industry-standard tools and methodologies for model training, statistical analysis, and machine learning deployment
- Experience working with CPG and ecommerce data sets, including retail analytics and advertising data, is a plus
- Candidates that have experience working with AMC (Amazon Marketing Cloud) and Amazon advertising and sales data will be given priority consideration
Benefits
- Performance-based incentives
- A competitive total rewards package, which includes a 401k with company match
- Healthcare coverage
- A broad range of other benefits
- Remote or hybrid role based on the selected candidate’s geographic location
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