Data Science Senior Analyst

hace 4 semanas

Miguel Hidalgo, México PepsiCo A tiempo completo

Overview:
**Are you passionate about shaping the future of data science and delivering impactful business solutions **on** a global scale?**

Join PepsiCo as a **Senior Data Science Analyst (Feature Engineering)** and become an integral part of our global data science team. In this role, you’ll be at the forefront of digital innovation, working across a diverse array of domains including consumer insights, revenue management, supply chain, manufacturing, and logistics. You will collaborate with a talented, interdisciplinary team of data professionals to develop and deploy advanced statistical and machine learning models, ensuring they are robust, scalable, and aligned with our strategic business goals.

Beyond your technical contributions, you’ll play a pivotal role in fostering a culture of innovation and continuous learning within the team. By championing data science best practices and working closely with process owners, product owners, and end-users, you'll ensure that our solutions are not only cutting-edge but also practical and valuable to the business. Your expertise will be instrumental in delivering insights that enhance consumer experiences, uncover revenue opportunities, and streamline operations.

As an advocate of data-driven decision-making and analytics excellence, you will stay current with the latest trends and advancements in data science and machine learning, incorporating relevant innovations into your work.** **By joining PepsiCo's Data & Analytics team, you will help transform data into impactful business solutions, driving innovation and fostering a culture of excellence in data science.**

**Responsibilities**:
**Your day-to-day with us**:
**Project **Participation**:

- Contribute to digital projects, collaborating with team members to ensure successful project execution.
- Assist in defining and integrating data science needs into product roadmaps.
- Support ML engineers in transitioning models to scalable, production-ready solutions.
- Provide data-based recommendations to influence product teams and drive strategic decision-making.

**Technical Expertise**:

- Ensure seamless data access and preparation for model development.
- Build and validate models to address complex business challenges.
- Support the adoption and use of the Platform toolset, showcasing 'the art of the possible' through demonstrations to business stakeholders as needed.

**Innovation and Research**:

- Actively participate in innovation activities, exploring and implementing cutting-edge data science techniques.
- Stay current with state-of-the-art methodologies, conducting research to integrate the latest advancements into the team’s work.
- Assist in large-scale experimentation, building and validating data-driven models to solve complex business problems.

**Collaboration and Coordination**:

- Assist product managers in understanding data science requirements and assessing DS components in roadmaps.
- Coordinate work activities with business teams, IT services, and other relevant stakeholders to ensure cohesive project progress and integration.

**Performance and Metrics**:

- Help define key performance indicators (KPIs) and metrics to evaluate the effectiveness of analytics solutions for specific use cases.
- Translate business requirements into well-defined modeling problems.

**Documentation and Standardization**:

- Document processes, findings, and developments comprehensively.
- Develop reusable packages or libraries to enhance efficiency and standardize practices.

Qualifications:
**What you will need to succed**:

- Minimum of 4 years of experience working in the **commercial, insights, revenue management, supply chain, manufacturing, or **logistics** sectors.**:

- 4+ years of experience working in a team to **deliver production-level analytic solutions**.
- 4+ years of experience in **ETL and/or data wrangling techniques. Fluent in SQL syntax.**:

- 2+ years of experience in **Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.**:

- 2+ years of experience in **developing business problem-related statistical/ML modeling** with industry tools, primarily focusing on Python or Scala development.
- Hands-on experience in **deploying machine learning models into production** and **working with large datasets.**:

- Experience with **big data technologies **like Spark, Hadoop, or similar frameworks.
- Familiarity with **cloud platforms **such as AWS, Azure, or Google Cloud.
- Fluent in **version control systems** like Git.

**What would be valued as a plus**:

- Understanding of **FAIR data principles** and **Responsible AI practices**.
- Familiarity with **Jenkins and Docker.**:

- ** Knowledge of advanced techniques** such as Reinforcement Learning, Simulation, Optimization, Bayesian methods, NLP, and distributed machine learning.
- Experience with **Deep Learning.**:

- Exposure to **data visualization tools** like Tableau, Power BI, or si

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