3 jobs found

WHAT YOU’LL DO  As a Data Engineer, you will work closely with a multidisciplinary agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights from our connected data, enabling General Mills to advance the data-driven decision-making capabilities of our enterprise. This role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows.  In this role you will:  Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.  Solve complex data problems to deliver insights that helps our business to achieve their goals  Create data products for analytics and data scientist team members to improve their productivity  Advise, consult, mentor and coach other data and analytic professionals on data standards and practices  Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions  Lead evaluation, implementation and deployment of emerging tools & process for analytic data engineering to improve our productivity as a team  Develop and deliver communication & education plans on analytic data engineering capabilities, standards, and processes  Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.  Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics WHO YOU ARE  Bachelor’s Degree  5 years of experience working in data engineering or architecture role Expertise in SQL and data analysis and experience with at least one programming language Experience developing and maintaining data warehouses in big data solutions  Big Data development experience using some or all of the following: Hive, BigQuery, Impala, Spark and familiarity with Kafka Experience working with BI tools such as Tableau, Power BI, Looker, Shiny  Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, structured and unstructured data.  Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics  Passion for agile software processes, data-driven development, reliability, and experimentation  Experience working on a collaborative agile product team   Excellent communication, listening, and influencing skills  WHAT’S NICE TO HAVE  Bachelor’s degree in Computer Science, MIS, or Engineering  7+ years applicable work experience Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space  Experience in Python or Scala  Big Data development experience using Hive, Impala, Spark and familiarity with Kafka  Familiarity with the Linux operating system   Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics Experience with OLAP such as AtScale, SSAS, SAP BW, Essbase Knowledge of Data Preparation, Data Wrangling, and Feature Engineering

WHAT YOU’LL DO: In order to make the food people love, we need to make sure we feed our decision makers the right data and solutions at the right time, every time. As a Senior Data Scientist at General Mills, you will apply your strong expertise in machine learning, data mining, and information retrieval to design, prototype and build next generation advanced analytics engine and services. You will collaborate with product owners, business partners and other Data Scientists in the consumer marketing and media space to define technical problem statement and hypothesis to test; develops efficient and accurate analytical models that mimic business decisions. In this role, you will: Collaborate with business partners to develop novel ways to optimize marketing levers, media mix, spend, etc. to meet goals utilizing cutting edge techniques and tools Educate cross-functional partners by effectively communicating your analytics approach in the marketing/media space Advocate and educate on the value of data-driven decision making, focusing on the “how and why” of solving problems Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers Engineer new features by using your business acumen to find new ways to combine disparate data sources Collaborate, coach, and learn with a growing team of experienced Data Scientists Stay connected with external sources of ideas through conferences and community engagements WHO YOU ARE: Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics and 5+ years’ experience required OR Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 2+ years work experience in a consumer, marketing, or media related role Must have Python or R proficiency working with DataFrames Must have proficiency writing complex SQL queries Must have proficiency with Machine Learning to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets Exceptional communication & collaboration skills to understand business partner needs & deliver solutions Bias for action, with ability to deliver outstanding results through task prioritization & time management WHAT’S NICE TO HAVE: Experience with Big Data technologies — Hadoop, Spark, H20.ai, Cloud AI platforms, containerization Experience with supporting deployment, monitoring, maintenance and enhancement of models Experience with data visualization tools — Tableau, R Shiny, Plotly, etc. Experience in digital marketing environment e.g. ad servers, web analytics, bid management Familiarity with digital marketing principles e.g. funnel optimization, landing page optimization Experience working in business to consumer marketing Experience using data to tell a story and influence business decision makers

WHAT YOU’LL DO: To make the food people love, we need to make sure we feed our decision makers the right data and solutions at the right time, every time. As a Senior Data Scientist at General Mills, you will apply your strong expertise in machine learning, data mining and information retrieval to design, prototype and build next generation advanced analytics engine and services. You will collaborate with product owners, business partners and other Data Scientists to define technical problem statement and hypothesis to test. In addition, you will develop efficient and accurate analytical models that mimic business decisions. In this role, you will: collaborate with business partners to develop novel ways to meet goals utilizing cutting edge techniques and tools and effectively communicating your analytics approach advocate and educate on the value of data-driven decision by focusing on the “how and why” of solving problems as your second nature lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers engineer new features by using your business acumen to find new ways to combine disparate data sources love to collaborate, coach and learn with a growing team of experienced Data Scientists stay connected with external sources of ideas through conferences and community engagements WHO YOU ARE: Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 5+ years’ experience required OR Graduate degree in quantitative discipline and demonstrated Data Science skill set, plus 2+ years work experience Must have Python or R proficiency working with DataFrames Must have proficiency writing complex SQL queries Must have proficiency with Machine Learning to solve problems such as clustering, classification, regression, anomaly detection, simulation and optimization problems on large scale data sets Exceptional communication and collaboration skills to understand business partner needs and deliver solutions Bias for action, with the ability to deliver outstanding results through task prioritization and time management WHAT’S NICE TO HAVE: Experience with Big Data technologies — Hadoop, Spark, H20.ai, Cloud AI platforms, containerization Experience with supporting deployment, monitoring, maintenance and enhancement of models Experience with data visualization tools — Tableau, R Shiny, Plotly, etc.