Data Scientist

The Data Scientist will play a critical role in analyzing complex datasets, developing machine learning models, and delivering actionable insights that drive business decisions. This role combines statistical analysis, data modeling, and problem-solving to create innovative solutions for business challenges. The Data Scientist will collaborate closely with stakeholders to identify opportunities for data-driven improvements and work alongside ML Pipeline Engineers to transition models into production.
This position requires a combination of technical expertise, curiosity, and business acumen to unlock the full potential of data.
RESPONSIBILITIES

• Perform exploratory data analysis (EDA) to uncover trends, anomalies, and patterns in complex datasets.
• Develop, test, and refine machine learning models and statistical analyses to address business challenges.
• Collaborate with business stakeholders to translate business questions into data science problems.
• Conduct feature engineering and feature selection to enhance model performance.
• Communicate insights and results through clear visualizations, dashboards, and presentations to non-technical stakeholders.
• Perform hypothesis testing, A/B testing, and statistical analyses to validate business strategies.
• Stay updated on the latest data science methods and tools, integrating new techniques to improve processes.
• Research and prototype algorithms to solve unique problems and perform proof-of-concept studies.
• Ensure data quality, integrity, and compliance with organizational and regulatory standards.

QUALIFICATIONS

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field, or equivalent experience.
• 4+ years of experience in data analysis, machine learning, and statistical modeling.
• Strong programming skills in Python, with experience in libraries like Pandas, NumPy, PyTorch , Scikit-learn, XGBoost.
• Proficiency in SQL for querying and manipulating data.
• Experience in building and evaluating machine learning models (regression, classification, clustering, etc.).
• Experience with classical and modern modeling methods including linear/logistic regression, random forests, boosted trees, and deep neural networks.
• Excellent communication skills to articulate technical results to non-technical stakeholders.

PREFERRED QUALIFICATIONS

• Familiarity with Azure and Snowflake.
• Experience with advanced modeling techniques like deep learning and time series forecasting.
• Prior experience in the transportation domain.

TOOLS AND TECHNOLOGY

• Python, and SQL for programming.
• Machine learning frameworks (Scikit-learn, XGBoost, PyTorch).
• Familiarity with version control systems like Git.

SOFT SKILLS

• Strong analytical and problem-solving abilities.
• Ability to work collaboratively with cross-functional teams.
• Excellent time management skills to prioritize multiple tasks effectively.
• Curiosity and eagerness to learn new techniques and technologies.