Remote Machine Learning Jobs 2023 by Mondelēz International

Last Updated on November 18, 2023 by GeeksGod

Off Campus Drive 2023

Remote Machine Learning Jobs 2023: You will be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business.  You will work with various stakeholders to determine how to use business data for business solutions/insights.

You will: Remote Machine Learning Jobs 2023

• Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization.  In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling
• Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business.  After that you will work with stakeholders to determine how to use business data for business solutions/insights
• Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results
• Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data
• Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy
• Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making
• Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements

What you will bring-Remote Machine Learning Jobs 2023

A desire to drive your future and accelerate your career and the following experience and knowledge:

• Strong quantitative skillset with experience in statistics and linear algebra.
• A natural inclination toward solving complex problems
• Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it
• Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons
• Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc.
• Good communication skills to promote cross-team collaboration
• Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc.
• Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders

A desire to drive your future and accelerate your career and the following experience and knowledge: 

• Deep understanding of Databricks or Apache Spark, running Python on Apache Spark through PySpark, MLOps practice through MLFlow 
• Good understanding of Google cloud applications likes of Google Big Query, Google Cloud Storage 
• Expertise in ETL activities, data movements across environments, data maintenance, and data management  
• To promote cross-team collaboration: Sharing and enforcing ‘good practices’ in code standardization, maintenance, data creation 
• Problem resolution mindset: A natural inclination toward solving technology problems such as code debugging, users access issue resolution, root cause analysis of system outage  
• Support Forecasting Solution Implementation for market for demand modelling in DataBricks & Spark and Model Forecast Improvement activity.  
• Broad understanding of the challenges a data scientist faces to run analytical machine learning jobs and  
• Owns responsibility of assigning and deploying clusters to ensure optimal run time of forecasting models 

More about this role: Remote Machine Learning Jobs 2023

What you need to know about this position: Remote Machine Learning Jobs 2023

The specialist will be responsible for the system level ownership of the delivery of forecast every cycle.  

• Databricks ownership: You will own end to end Databricks solution including dev/prod separation, monitoring of the cost and efficiency 
• Maintaining system architecture: Co-ordinating and ensuring best practice for System level tasks such as : naming convention (table, column), structure of the library as per the best practice  
• Create code blueprints: navigate the forecasting team in the performance optimization on Spark cluster, guide on best libraries, code blueprints 
• Scaling and cost control: Optimize the cluster scaling (horizontal and vertical) against the cost   
• Manage and Govern code: Own the responsibilities of coding best practice by individual data scientists and implement principles of interoperability, modularity and scalability 
• Overall ETL process ownership: Code review / Quality of the code management, Optimization (including Google Big Query, Spark), Code merge from different modellers, Release preparation 
• Collaborate with DS and Project / Enterprise IT: Need to represent Data science team in technical discussion with (upstream and downstream of the platform) IT team and operationalize the code from ‘experimental’ zone to ‘deployment’  
• On-boarding new country: Depending on the complexity of the process and structure of the data this role will ensure sustainability of the overall process and orchestrate the change 
• Version Upgrade: In case of impact on existing set-up (code, jobs) due to version upgrade, the role will be assessing the impact and fix it (occasional)  
• Job load managing: at the system level decide the number of parallel jobs and impact on modelling approach/ data change 

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