Data Scientist - Avanciers : Job Details

Location: Bay Area , CA / Reno, NV. No remote

Duration: 12 months

Start Date : Immediate

Worked at a Trucking/Logistics/Freight companies: Uber Freight, Con-way, CH Robinson, Coyote Logistics, Flexport are some examples

JD

Key Responsibilities:

· Analyzing data patterns and trends through statistical methods to understand the underlying relationships within the data

· Deep understanding of statistical modeling, machine learning algorithms, analytics concepts, and a track record of solving problems

· 5 years of experience with developing ML models

· Prior experience in ML modeling using TensorFlow, Pytorch

· Model Development: Develop and deploy machine learning algorithms & models using Python and relevant libraries/frameworks

· Data Preprocessing, Address missing data, outliers, and anomalies using Databricks' robust data processing tools

· Feature Engineering Development

· Training Validation, Model Experimentation and Model Selection

· Hyper parameter tuning

· Presenting complex data insights through compelling visualizations like charts, graphs, and dashboards to effectively communicate findings to stakeholders

· Interpreting data insights and translating them into actionable business recommendations

Minimum Requirements:

Education: Bachelor's degree in computer science, Statistics, Mathematics, or related field.

Experience:

• Minimum of 3 years of experience in data science - centric roles with a strong focus on analytics, data science, and machine learning.
• Experience as Data Scientist in Freight / Logistics Industry is must.

Technical Skills:

· Proficiency in Python, SQL, or PySpark with strong programming skills

· Strong understanding of machine learning algorithms, model evaluation, and optimization techniques

· Proven track record of developing and deploying models in Production

Analytical Skills:

• Robust analytical and problem-solving skills with a solid foundation in statistical methods.
• Expertise in translating business issues into data-driven solutions using Databricks.