Les Schwab Tire Center

Born in 1917 in Bend, Oregon, Les Schwab came from humble beginnings. He was a self-made man, and believed in old-fashioned hard work. Les built his business from one store to hundreds of locations across the western states, making Les Schwab one of the largest independent tire businesses in the United States.

He didn’t do it alone. Les valued partnership — he was married for over 70 years after all — and provided his employees training and opportunities to grow and succeed, both financially and personally. Les believed in treating customers like family.

Although Les passed away in 2007, his vision remains at the core of the company’s culture: give people more for their money … reward employees for their expertise and hard work … earn people’s trust and everyone benefits. Today, the 7,000+ employees of Les Schwab Tire Centers are proud to carry on this legacy.

Les Schwab Tire Center Bend, OR, USA
Sep 21, 2019
It’s time to really be a part of something. Work is so much more than just showing up, it should be an experience, one that has an opportunity to make a difference, impact others and grow professionally while also having a better life outside of work. Working at Les Schwab means you won’t just be getting by. You’ll be thriving—doing great work, on a team of talented people, with a supportive work environment, in a beautiful location. We started in 1952 when Les Schwab bought one tire store in Central Oregon. Since then, we have remained true to Les Schwab's vision of World Class Customer Service and unsurpassed benefits and opportunity to our employees. Today, we have over 400 locations including Retail Tire Stores, Distribution Centers, Production, Transport, Equipment, and Headquarters. ABOUT THE OPPORTUNITY The Marketing and Customer Insights Analyst at Les Schwab is responsible for researching and identifying ways to build our brand and to acquire, convert and retain customers. Marketing and Customer Insights Analyst responsibilities include tracking advertising costs, analyzing consumer behavior and exploring market trends and opportunities. To be successful in this role, this person should have 5-10 years of experience with processing and analyzing marketing and customer data. The Marketing Analyst position requires a strong knowledge of web analytics, campaign optimization, data visualization, return on ad spend calculation, forecasting and the ability to derive trends and insights from large data sets. This position will participate in the development of standard measures, methodology, and processes for campaign analysis and attribution. The Analyst will work with teammates and business stakeholders to understand requirements, then develop and execute plans to produce meaningful insight. The Marketing and Customer Insights Analyst will take a customer-first approach to analysis; understanding customer needs indicated by data, and recommending ways to meet those needs. The position will be located at our state of the art headquarters in beautiful Bend, Oregon and will report directly to the Director, Customer Experience. PRIMARY RESPONSIBILITIES Measure the effectiveness of marketing programs and strategies and provide insightful data-driven guidance on regional promotional targets and what future marketing tactics will provide growth. Manage the monthly program review reporting, consolidating data points and performance summaries for presentation to executive leadership; while working with Les Schwab Business Intelligence team to automate recurring reporting into Birst/Tableau. Work closely with the Marketing and Product teams to identify opportunities for new customer acquisition and existing customer retention. Monitor and improve reporting around customer profile, key segments, Recency/Frequency/Monetization Analysis. Work closely with the Les Schwab Business Intelligence team to build, maintain, and modify customer acquisition and retention analyses that calculate lifetime value. Conduct competitive research and analyze benchmarking data. MINIMUM EDUCATION & SKILLS REQUIRED Bachelors’ degree with a focus in statistics or analysis; MBA a plus. 5+ years marketing and customer analysis experience in a retail environment. Experience in automotive retail environment is preferable. REQUIRED TECHNICAL SKILLS/KNOWLEDGE Advanced Excel user and strong overall systems knowledge (Such as CRM systems, SQL, Snowflake, Statistical analysis, Birst, Tableau, Google Analytics, SalesForce Marketing and Commerce Clouds). Comfortable working in the Google G Suite (Gmail, Docs, Sheets, Slides). GENERAL KNOWLEDGE AND ABILITIES Very strong analytical skills a must with emphasis on interpreting marketing & sales data to provide return on ad spend analysis. Advanced mathematical skills with a demonstrated ability to perform calculations and financial analysis of moderately complex data. Ability to analyze marketing metrics to identify cause and effect relationships that explain historical trends to allow development of dynamic forecasts. Excellent communication, interpersonal and proven business partnership skills with a bias towards strategic thinking. Articulate findings to stakeholders and executives using strong written and verbal presentation and communication skills. Organized, accurate, detail-oriented, ability to multitask, and balance multiple priorities.
Les Schwab Tire Center Bend, OR, USA
Sep 21, 2019
Phenomenal opportunity with an industry leader! We started in 1952 when Les Schwab bought one tire store in Central Oregon. Since then, we have remained true to Les Schwab's vision of World-class Customer Service and unsurpassed benefits and opportunity to our employees. Today, we have over 480 locations including Retail Tire Stores, Distribution Center, Production, Transport, Equipment, and Headquarters. We have a collaborative, high-energy work environment where team members are empowered to “run with” ideas to improve processes. As the largest tire dealer in the western states, you will play a key role in transforming structured and unstructured data into insights and models for business decision-making. We look for candidates who are not satisfied with the status quo, are intellectually curious and confident in their abilities. If you are looking to join a dynamic, exciting and growing leader, consider Les Schwab! You will report to the Portfolio Manager and will be based out of our headquarters in Bend, OR.  About the opportunity The Data Scientist I performs individual work assignments, participates in working groups and contributes to enterprise projects. For each assignment the Data Scientist I utilizes business consulting skills to frame business problems and transform them into analytical problems to be solved using appropriate data science methods. The Data Scientist I leverages appropriate tools for accessing and cleansing data, developing code, building predictive models, and applying statistical methods to achieve solutions to be validated by the business. The Data Scientist I has the ability to quickly learn and comprehend new concepts. This position requires some supervision delivering outcomes, a low level of breadth/depth of job specific knowledge and an average level of service delivery, professionalism, and communication. Primary responsibilities/functions you are responsible for: Conduct data science: Execute discovery processes of low to average complexity with stakeholders to define the business problem, understand IT/business constraints and opportunities. Understand the qualitative nature of data required to deliver results. Transform the business problem into an analytical problem and identify data science approaches for achieving the desired business insights. Build data pipelines from sources including internal data (i.e., point-of-sale, ERP and financial systems, websites, etc.) and external data (i.e., weather stations, geo-location systems and social media sites). Apply data cleansing techniques such as deduplication, hashing, scaling and normalization, dimensionality reduction, fuzzy matching, imputation and cross-validation. Design experiments to gain insight and test hypotheses using quantitative methods. Apply various Machine Learning (ML) and advanced analytics techniques to perform classification or prediction tasks. Present insights and rationale of recommendations in easy to understand terms; guide business stakeholders to validate insights and recommendations. Collaborate with data engineers and IT to evaluate and implement deployment options for developed models. Identify the lifecycle of any developed models and insights and develop maintenance plans for ongoing operational use of insights and recommendations. Contribute to Data Science and BI Team effectiveness: Create reusable artifacts and contribute to data and insight catalogues and documentation Participate in peer reviews and presentation of specialist data science topics to advance collective team understanding of relevant technologies and techniques to accomplish data science outcomes Network within IT and business partner departments to gain business understanding Proactively engage in continuous professional improvement in both technical and soft skills Contribute to BI Portfolio effectiveness: Partner with data stewards and data platform developers in continuous improvement processes to help improve data quality Recommend ongoing improvements to data capture methods, analysis methods, mathematical algorithms, etc. that lead to better outcomes and quality. Contribute to group retrospectives and improvement of processes for collective work management Qualifications: Educational/Experience Requirements:  Bachelor’s degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field.  Alternate experience and education in equivalent areas such as economics, engineering or physics is acceptable.  Master’s degree preferred Certified Analytics Professional credential (available through INFORMS.ORG) preferred AND minimum of two (2) years of full-time or equivalent relevant experience executing data science projects, preferably in the domains of customer behavior prediction and operations management. Required Technical Skills/Knowledge:  Substantial coding knowledge and experience in at least two programming languages: for example, R, Python/Jupyter, C/C++, Java or Scala. Experience with database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NOSQL/Hadoop-oriented databases. Knowledge and experience in statistical and data mining techniques that include generalized linear model (GLM) / regression, random forest, boosting, trees, text mining, hierarchical clustering, neural networks, graph analysis, data sampling, design of experiments, etc.  Familiarity with typical algorithms used by retail businesses (i.e., Churn, Segmentation) preferred. Technical skills for working across multiple deployment environments including cloud, on-premises and hybrid and skills for acquiring new datasets, parsing datasets, organizing datasets, representing data visually and automating data-driven models.  Experience with statistical tools and advanced analytics platforms such as: Minitab, SAS, Knime, Dataiku, Anaconda, Google Collaboratory. General Knowledge and Abilities:  Analytical Skills : Strong analytical and problem-solving skills  Communication : Ability to communicate technical and non-technical/complex information clearly and professionally (both verbally and in writing) while ensuring that the quality and content of the message are relevant to the circumstances and understandable to wide audiences; ability to be an active-listener; the ability to draft, proofread, and send written communications effectively; the ability and willingness to carefully listen to others by asking appropriate questions and avoiding interruptions Confidentiality : Ability to work with confidential data, effectively and with discretion with all staff levels Flexibility : Willingness to work in an ever-changing environment with the ability to positively adapt to organizational, process, and technology changes Initiative : Self-driven, curious and creative Multitasking : The ability to perform two or more tasks simultaneously or to shift back and forth between two or more activities or sources of information without difficulty Organization : Ability to manage work assignments through prioritization, paying attention to detail, and optimal time management Service Excellence : Exhibit the willingness to be stakeholder-focused by anticipating and understanding stakeholders' needs; collaborate with them to reach a suitable solution; then consistently meet and deliver on those expectations Teamwork : The ability to establish and maintain rapport, interact comfortably, and work well with coworkers. This includes cooperating, being supportive of others, willingly helping others, considering others’ ideas and opinions, sharing information, giving proper credit, and fulfilling team responsibilities and the professionalism to collaborate cross-functionally
Les Schwab Tire Center Bend, OR, USA
Sep 21, 2019
Phenomenal opportunity with an industry leader! We started in 1952 when Les Schwab bought one tire store in Central Oregon. Since then, we have remained true to Les Schwab's vision of World-class Customer Service and unsurpassed benefits and opportunity to our employees. Today, we have over 480 locations including Retail Tire Stores, Distribution Center, Production, Transport, Equipment, and Headquarters. We have a collaborative, high-energy work environment where team members are empowered to “run with” ideas to improve processes. As the largest tire dealer in the western states, you will play a key role in transforming structured and unstructured data into insights and models for business decision-making. We look for candidates who are not satisfied with the status quo, are intellectually curious and confident in their abilities. If you are looking to join a dynamic, exciting and growing leader, consider Les Schwab! You will report to the Portfolio Manager and will be based out of our headquarters in Bend, OR.  About the opportunity The Data Scientist II performs individual work assignments, participates in working groups and contributes to enterprise projects, often independently representing the Data Science and BI Team. The Data Scientist II has a strong business acumen and ability to frame business problems and transform them into analytical problems to be solved using appropriate data science methods. The Data Scientist II has a breadth of expertise in data science methodologies and techniques and can select appropriate tools for accessing and cleansing data, develop code, build predictive models, and apply statistical methods to achieve solutions to be validated by the business. This position requires minimal supervision delivering outcomes, a high breadth/depth of job specific knowledge and an advanced level of service delivery, professionalism, and communication. Primary responsibilities/functions you are responsible for: Conduct data science: Lead discovery processes of high complexity with stakeholders to define the business problem, understand IT and business constraints and opportunities and understand the qualitative nature of data required to deliver results. Transform the business problem into an analytical problem and identify a wide breadth of data science approaches for achieving the desired business insights and criteria for selecting among approaches. Build data pipelines from sources including internal data (i.e., point-of-sale, ERP and financial systems, websites, etc.) and external data (i.e., weather stations, geo-location systems and social media sites). Apply data cleansing techniques such as deduplication, hashing, scaling and normalization, dimensionality reduction, fuzzy matching, imputation and cross-validation. Design experiments to gain insight and test hypotheses using quantitative methods. Apply various Machine Learning (ML) and advanced analytics techniques to perform classification or prediction tasks. Present insights and rationale of recommendations in easy to understand terms; guide business stakeholders to validate insights and recommendations; maintain an ability and willingness to present analysis results that are data driven and may contradict common belief. Collaborate with data engineers and IT to evaluate and implement deployment options for developed models. Identify the lifecycle of any developed models and insights and develop maintenance plans for ongoing operational use of insights and recommendations. Contribute to Data Science and BI Team effectiveness: Assist the Data Science and BI team lead in creating high quality summaries of Data Science projects and results for presentation to steering committees and executive groups Assist the Data Science and BI team lead in scoping and prioritizing data science projects Create reusable artifacts and contribute to data and insight catalogues and documentation Be a lead participant in peer reviews and presentation of specialist data science topics to advance collective team understanding of relevant technologies and techniques to accomplish data science outcomes Network within IDS and business partner departments to gain business understanding Proactively engage in continuous professional improvement in both technical and soft skills Contribute to BI Portfolio effectiveness: Partner with data stewards and data platform developers in continuous improvement processes to help improve data quality Recommend ongoing improvements to data capture methods, analysis methods, mathematical algorithms, etc. that lead to better outcomes and quality. Contribute to group retrospectives and improvement of processes for collective work management Help improve enterprise stakeholder understanding of related technologies and processes to accomplish data science outcomes Guide and inspire others about the potential applications of data science Qualifications: Educational/Experience Requirements:  Bachelor’s degree in applied mathematics, statistics, computer science, operations research, or a related quantitative field.  Alternate experience and education in equivalent areas such as economics, engineering or physics is acceptable.  Master’s degree preferred  Certified Analytics Professional credential (available through INFORMS.ORG) required AND minimum of 3-6 years of full-time or equivalent relevant experience executing data science projects, preferably in the domains of customer behavior prediction and operations management. Required Technical Skills/Knowledge:  Advanced coding knowledge and experience in at least two programming languages: for example, R, Python/Jupyter, C/C++, Java or Scala. Advanced knowledge of database programming languages including SQL, PL/SQL, or others for relational databases, graph databases or NOSQL/Hadoop-oriented databases. Broad Knowledge and experience in statistical and data mining techniques that include generalized linear model (GLM) / regression, random forest, boosting, trees, text mining, hierarchical clustering, neural networks, graph analysis, data sampling, design of experiments, etc.  Familiarity with typical algorithms used by retail businesses (i.e., Churn, Segmentation) required. Technical skills for working across multiple deployment environments including cloud, on-premises and hybrid and skills for acquiring new datasets, parsing datasets, organizing datasets, representing data visually and automating data-driven models.  Advanced knowledge of statistical tools and advanced analytics platforms such as: Minitab, SAS, Knime, Dataiku, Anaconda, Google Collaboratory General Knowledge and Abilities:  Analytical Skills : Strong analytical and problem-solving skills  Communication : Ability to communicate technical and non-technical/complex information clearly and professionally (both verbally and in writing) while ensuring that the quality and content of the message are relevant to the circumstances and understandable to wide audiences; ability to be an active-listener; the ability to draft, proofread, and send written communications effectively; the ability and willingness to carefully listen to others by asking appropriate questions and avoiding interruptions Confidentiality : Ability to work with confidential data, effectively and with discretion with all staff levels Flexibility : Willingness to work in an ever-changing environment with the ability to positively adapt to organizational, process, and technology changes Initiative : Ability to work effectively with minimal supervision with proven ability to execute high/very high complexity and diversity of work assignments Multitasking : The ability to perform two or more tasks simultaneously or to shift back and forth between two or more activities or sources of information without difficulty Organization : Ability to manage work assignments through prioritization, paying attention to detail, and optimal time management Service Excellence : Exhibit the willingness to be stakeholder-focused by anticipating and understanding stakeholders' needs; collaborate with them to reach a suitable solution; then consistently meet and deliver on those expectations Teamwork : The ability to establish and maintain rapport, interact comfortably, and work well with coworkers. This includes cooperating, being supportive of others, willingly helping others, considering others’ ideas and opinions, sharing information, giving proper credit, and fulfilling team responsibilities and the professionalism to collaborate cross-functionally credit, and fulfilling team responsibilities and the professionalism to collaborate cross-functionally