Data Scientist
Irvine, CA, US, 92606
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 will play an important role in executing data analysis for Kia North America’s regional subsidiaries (KUS/KCA/KaGA/KMX). A future-driven automotive company, Kia has access to vast and diverse datasets and is excited to fill this position with an individual that can derive business improvements and insights from this data. Strong applicants for this role will have statistics, machine learning, and computer science skills to leverage high-performance compute clusters as well as perform reproducible data analysis at scale. With these requirements in mind, our mindset is that data, analytics, automation, and responsible AI can revolutionize our many lines of business.
Essential Duties and Responsibilities
1st Priority - 30%
Data wrangling and analysis
- Assess the accuracy of new data sources
- Understand the relationship between the data and the business process
- 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
2nd Priority - 30%
Assess, visualize, and improve analysis
- Test and continuously improve the accuracy of statistical and machine learning models
- Present information using Python notebooks and/or dashboards
- Simplify and explain complex statistics in an intuitive manner
- 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
Qualifications/Education
Education:
- Bachelor’s degree or equivalent experience in related field of technology required
- Master’s degree in analytics, data science, or computer science preferred
Job Requirement
Overall Related Experience:
- Experience querying databases and using programming languages such as Python and SQL
- Experience using Hadoop ecosystem (Hadoop, Hive, Impala and Spark etc.)
- Experience using statistics, machine learning and deep learning algorithms
- Experience publishing results to stakeholders through dashboards (e.g. Power BI, MicroStrategy, Tableau)
Directly Related Experience:
- 3+ years of experience in data science preferred
Specialized Skills and Knowledge Required
- Proficiency in Python and SQL
- Knowledge of a variety of machine learning techniques including deep learning
- Knowledge of advanced statistical techniques
- Knowledge and experience with natural language processing (NLP)
- 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 stats models and Scikit-learn
- Experience with deep learning frameworks such as PyTorch and TensorFlow
- Experience with big data processing tools: Hadoop ecosystem, Spark etc.
- 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
$82,382 - $110,272
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.
Nearest Major Market: Irvine California
Nearest Secondary Market: Los Angeles