Data Scientist II

Lennox InternationalRichardson, TX
3d$88,000 - $115,500

About The Position

Lennox (NYSE: LII) Driven by 130 years of legacy, HVAC and refrigeration success, Lennox provides our residential and commercial customers with industry-leading climate-control solutions. At Lennox, we win as a team, aiming for excellence and delivering innovative, sustainable products and services. Our culture guides us and creates a workplace where all employees feel heard and welcomed. Lennox is a global community that values each team member’s contributions and offers a supportive environment for career development. Come, stay, and grow with us. What Drives Success General duties of this position will entail the following: Organizes, analyzes and extracts meaningful information from large amounts of data to build a learning machine which helps in streamlining business processes. Assists on machine learning projects that use and promote data-exploration techniques to discover new or previously unasked questions. Builds custom data-fueled models and algorithms, uses machine learning tools and statistical techniques to improve decision making capabilities, produce solutions to problems and improve ROI. Builds custom data models and algorithms to complex data sets Works on a broad range of Data Science problems across varied business groups. Develops expertise in various businesses and help translate that into increasingly high value added advisory solutions to stakeholders. Works with others to develop, refine and scale data management and analytics procedures, systems, workflows, best practices and other issues to contribute to the company’s machine learning practice.

Requirements

  • Requires a bachelor's degree in a related field (Business, Computer Science, Information Science, Analytics) or an equivalent combination of education and experience.
  • Requires at least 1 year related experience.
  • Working knowledge of statistical computer languages, such as R, Python, SQL, and PySpark, to manipulate data and interpret insights from large data sets.
  • Good understanding of machine learning techniques such as clustering, decision trees, Random Forest, logistic regression, linear regression, gradient boosted trees, and Naive Bayes classifier.
  • Good knowledge of visual analytics, with preferable experience of Qlik, Tableau or PowerBI.
  • Good understanding of big data architecture and how distributed computing works.
  • Working knowledge of database concepts and ability to handle large complex data sets.
  • Ability to communicate results and gain consensus with non-technical audience.
  • Some experience with SparkMlib combined with strong programming background.
  • Working knowledge about analyzing unstructured information.

Responsibilities

  • Organizes, analyzes and extracts meaningful information from large amounts of data to build a learning machine which helps in streamlining business processes.
  • Assists on machine learning projects that use and promote data-exploration techniques to discover new or previously unasked questions.
  • Builds custom data-fueled models and algorithms, uses machine learning tools and statistical techniques to improve decision making capabilities, produce solutions to problems and improve ROI.
  • Builds custom data models and algorithms to complex data sets
  • Works on a broad range of Data Science problems across varied business groups.
  • Develops expertise in various businesses and help translate that into increasingly high value added advisory solutions to stakeholders.
  • Works with others to develop, refine and scale data management and analytics procedures, systems, workflows, best practices and other issues to contribute to the company’s machine learning practice.

Benefits

  • tuition reimbursement
  • medical, dental, and vision insurance
  • prescription drug coverage
  • 401(k) retirement plan
  • short-term disability insurance
  • 8 weeks paid birthing leave
  • 2 weeks paid bonding leave
  • life and long-term disability insurance
  • 12 days paid time off
  • 2 paid well-being days
  • 1 paid volunteer day
  • 12 paid holidays
  • 3 floating holidays per year
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