Job description

At Kia, we’re creating award-winning products and redefining what value means in the automotive industry. It takes a special group of individuals to do what we do, and we do it together. Our culture is fast-paced, collaborative, and innovative. Our people thrive on thinking differently and challenging the status quo. We are creating something special here, a culture of learning and opportunity, where you can help Kia achieve big things and most importantly, feel passionate and connected to your work every day. Kia provides team members with competitive benefits including premium paid medical, dental and vision coverage for you and your dependents, 401(k) plan matching of 100% up to 6% of the salary deferral, and paid time off. Kia also offers company lease and purchase programs, company-wide holiday shutdown, paid volunteer hours, and premium lifestyle amenities at our corporate campus in Irvine, California. Status Exempt General Summary The Data Scientist plays an important role in executing data analysis for Kia North America’s regional subsidiaries (KUS/KCA/KaGA/KMX). Kia’s Big Data Analysis team leverages vast and diverse datasets to drive business improvements and insights. The role requires expertise in statistics, machine learning, and computer science to utilize high-performance compute clusters and perform reproducible analyses at scale. This position supports the application of data, analytics, automation, and responsible AI to advance Kia’s business operations. This role focuses on using data and machine learning to answer complex business questions, build analytical and predictive models, and translate results into clear insights and recommendations for stakeholders. The role goes beyond reporting by framing problems, designing analyses, and influencing decisions. Essential Duties and Responsibilities 1st Priority - 30% Business Problem Framing, Data Wrangling & Analysis • Assess the accuracy of new data sources • Understand business processes and decision frameworks, and translate them into data-driven metrics and KPIs. • Preprocess structured and unstructured data • Analyze large amounts of data to discover trends and patterns • Build prediction and classification models • Coordinate with different functional teams for feature engineering • Partner with business stakeholders to frame problems, define success metrics, and translate business questions into analytical approaches 2nd Priority - 30% Insight Generation, Visualization & Model Improvement • Test and continuously improve the accuracy of statistical and machine learning models • Present insights in a way that clearly ties analysis to business decisions and actions • Frame and communicate complex analyses in business-relevant terms that non-technical stakeholders can understand and act on • Continuously monitor and validate production analysis results 3rd Priority - 20% Collaborate with IT Team to deploy analysis results • Build REST APIs for data and analysis result consumption • Assist the IT system developers to deploy analysis as a service 4th Priority - 20% Clear documentation, source code management, and reproducible analysis • Use git within GitLab • Create virtual environments to isolate project dependencies and requirements • Track model performance and hyperparameter configurations • Track data versioning This list of essential responsibilities and duties is not exhaustive and may be supplemented and changed as necessary by management. Qualifications/Education Education: • Bachelor’s degree in a quantitative field required (e.g., Data Science, Statistics, Computer Science, Engineering, Economics, Mathematics, Business Analytics, or related field) • Master’s degree in a quantitative field preferred Job Requirement • 3+ years of experience in data science preferred. • Strong data analysis and statistical foundations required. • Proficiency in Python and SQL required. • Familiarity with applied machine learning concepts required. • Strong business acumen and ability to coordinate between technical teams and non-technical business stakeholders. • Experience querying databases and using programming languages such as Python and SQL • Experience using statistics and machine learning algorithms • Experience with big data processing frameworks such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms (e.g., Databricks, AWS) preferred • Experience publishing results to stakeholders through dashboards (e.g. Power BI, MicroStrategy, Tableau) Specialized Skills and Knowledge Required • Proficiency in Python and SQL • Knowledge of a variety of machine learning techniques, deep learning a plus • Knowledge of advanced statistical techniques • Experience with common Python libraries for data analysis such as Pandas and NumPy • Experience with visualization libraries such as Matplotlib, Seaborn, Plotly, Bokeh and plotnine • Experience developing and evaluating statistical and machine learning models using libraries such as statsmodels and scikit-learn • Experience with big data processing tools such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms preferred • Experience with deep learning frameworks such as PyTorch and TensorFlow preferred • Strong data-driven problem-solving skills • Excellent written and verbal communication skills to coordinate across teams Competencies • Care for People • Chase Excellence Every Day • Dare to Push Boundaries • Empower People to Act • Move Further Together Pay Range $89,936 - $121,409 Pay will be based on several variables that are unique to each candidate, including but not limited to, job-related skills, experience, relevant education or training, etc. Equal Employment Opportunities KUS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, ancestry, national origin, sex, including pregnancy and childbirth and related medical conditions, gender, gender identity, gender expression, age, legally protected physical disability or mental disability, legally protected medical condition, marital status, sexual orientation, family care or medical leave status, protected veteran or military status, genetic information or any other characteristic protected by applicable law. KUS complies with applicable law governing non-discrimination in employment in every location in which KUS has offices. The KUS EEO policy applies to all areas of employment, including recruitment, hiring, training, promotion, compensation, benefits, discipline, termination and all other privileges, terms and conditions of employment. Disclaimer : The above information on this job description has been designed to indicate the general nature and level of work performed by employees within this classification and for this position. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.

Requirements

Must-haves

General Summary
Essential Duties and Responsibilities
1st Priority - 30%
Business Problem Framing, Data Wrangling & Analysis
Assess the accuracy of new data sources
Understand business processes and decision frameworks, and translate them into data-driven metrics and KPIs.
Preprocess structured and unstructured data
Analyze large amounts of data to discover trends and patterns
Build prediction and classification models
Coordinate with different functional teams for feature engineering
Partner with business stakeholders to frame problems, define success metrics, and translate business questions into analytical approaches
2nd Priority - 30%
Insight Generation, Visualization & Model Improvement
Test and continuously improve the accuracy of statistical and machine learning models
Present insights in a way that clearly ties analysis to business decisions and actions
Frame and communicate complex analyses in business-relevant terms that non-technical stakeholders can understand and act on
Continuously monitor and validate production analysis results
3rd Priority - 20%

Nice-to-haves

Master’s degree in a quantitative field preferred
3+ years of experience in data science preferred.
Experience with big data processing frameworks such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms (e.g., Databricks, AWS) preferred
Knowledge of a variety of machine learning techniques, deep learning a plus
Experience with big data processing tools such as Spark (e.g., PySpark); experience with Hadoop ecosystem or cloud platforms preferred
Experience with deep learning frameworks such as PyTorch and TensorFlow preferred

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Keywords to mirror

machine learningairestpythonsqlaws

Platform: successfactors
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off