Posted in Other 30+ days ago.
Type: Full Time
Tesla's mission is to accelerate the world's transition to sustainable energy. Tesla s Finance Analytics team supports this mission by converting raw data into actionable insights and automation through the following disciplines:
* Financial analysis - build automated financial models, conduct ad-hoc analysis, and make recommendations to management
* Business intelligence - increase data visibility and access for business teams through the creation and curation of data platforms and tools including Tesla's data warehouse, operational reports, self-service data models, and managerial dashboards
* Data engineering - build and manage data pipelines and analytical database architecture
* Data science - conduct statistical analysis and train machine learning models to inform and control financial decisions
* Back-end engineering - build and manage a collection of microservices to scale core business processes and integrate with enterprise systems
We are committed to hiring the world's best and brightest people who can sit at the intersection of multiple of these disciplines and are passionate about continuing to develop their skills further. We believe that small agile teams using modern development stacks and comprised of diverse members with complementary skill sets can have an outsized impact in driving better decisions and automating core business processes.
We are looking for a talented data scientist to conduct advanced statistical analysis across predictive, descriptive, diagnostic, and prescriptive applications within the business:
* Predictive (what is likely to happen*): Train and manage machine learning models for applications in forecasting (cash flow, demand, revenue, spend), pricing (trade-in/used car valuation models, elasticity models), risk management (credit, lease, and insurance underwriting, residual value models, fraud detection), and data quality (anomaly detection, data recommendation). Partner closely with application engineering teams to deploy models as APIs for integration within Tesla's application ecosystem.
* Descriptive (what happened/is happening*): Partner with the business intelligence, data engineering, and fleet analytics teams to deliver descriptive analytics for the business with a special focus on large, complex data sets where distributed database platforms and computing tools are required (ex. telemetry data from factory, superchargers, vehicles, and energy products). Communicate insights using open-source data visualization libraries and frameworks.
* Diagnostic/Prescriptive (why did this happen*/what should we do*): Conduct ad-hoc analysis for the business, performing rigorous analysis on diverse datasets using inferential and optimization models, translating results into business recommendations.
* BS/MS/PhD in STEM or quantitative field (CS, Applied Statistics, Econometrics, Operations Research) or BS/MBA in Finance, Accounting, Economics, Business Analytics (preferred both)
* Applied statistics and machine learning experience (regression analysis, time series, probabilistic models, supervised and unsupervised methods)
* Proficiency in Python and experience with open-source ML libraries and frameworks like Scikit-learn, PyTorch, and Tensorflow
* Proficiency in SQL and experience with commercial and emerging databases, technologies, and languages
* Proficiency in data processing, cleansing, and verifying the integrity of data used for analysis and data enrichment with third party data sources when needed
* Proficiency in feature engineering and the ability to choose the right tool and analytical method appropriate for the complexity of the problem, balancing between speed, accuracy, and interpretability
* Experience with data visualization libraries and frameworks like Matplotlib, Seaborn, Plotly, D3.js, etc
* Ability to self-start and self-direct work in an unstructured environment, comfortable dealing with ambiguity
* Excellent problem-framing, problem solving and project management skills and ability to change direction quickly
* Excellent communication and interpersonal skills, ability to present to senior management and non-technical stakeholders
* Experience with open-source data technologies including Hadoop, Spark, Kafka, and Presto
* Experience with self-service data visualization tools (Tableau, PowerBI, Superset)
* Experience with Airflow
* Experience with git and version control workflows
* Experience deploying ML models as APIs in a production environment
* Experience with containers (Docker, Kubernetes)
* Experience with application development frameworks (Flask, Django)
* Knowledge of various data communication protocols (REST API, Websockets)
* Experience with CI/CD (Jenkins, Concourse, or similar)
* Experience with public cloud environments (AWS, Azure, GCP)
* Experience working with financial systems and basic knowledge of accounting principles, financial statements, and financial modeling
Tesla participates in the E-Verify Program
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.