W2 :: Lead Data Scientist :: Columbus, Ohio (Hybrid)

Overview

On Site
Full Time
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 6 Month

Skills

Banking
Customer Support
Visualization
Analytical Skill
Research
Deep Learning
Artificial Intelligence
Analytics
Sourcing
Presentations
Leadership
Coaching
Mentorship
Data Analysis
Predictive Modelling
Unstructured Data
FOCUS
Cloud Computing
Amazon SageMaker
TensorFlow
scikit-learn
Data Science
R
RStudio
Python
SAS
Database Architecture
SQL
NoSQL
Financial Services
Machine Learning (ML)
Scripting
Big Data
Web Scraping
Linear Regression
Modeling
Computer Science
Statistics
Economics
LinkedIn
Oracle UCM

Job Details

Job Title Lead Data Scientist

Location Columbus, Ohio (Hybrid)

Duration 6 Month

Proper LinkedIn

W2 only

Job Description :-

Overview:

Our Enterprise Data and Analytics team is growing. We're looking for a Lead Data Scientist to assist with building and developing our Data Science team and lead us into the next generation of banking. We are reimagining how data is used across the bank to better serve our customers, support our communities, and make our colleagues lives better. Our goal is to be the best performing Regional Bank in America, and we need data and analytics to meet that goal.

As we advance our data science and analytics capabilities, we want a Lead Data Scientist to develop experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. We are looking for a leader who has a passion for developing others, driving change, and continuously improving and evolving the application of technologies to meet todays and tomorrow's challenges.

Responsibilities:

  • Prioritizes analytical projects based on business value and technological readiness
  • Performs large-scale experimentation and build data-driven models to answer business questions
  • Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
  • Evangelizes best practices to analytics and products teams
  • Acts as the go-to resource for machine learning across a range of business needs
  • Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring
  • Provides leadership, coaching, and mentoring to team members and develops the team to work with all areas of the organization
  • Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs
  • Anticipates and analyzes trends in technology while assessing the emerging technology's impact(s)
  • Coaches' individuals through change and serves as a role model

Skills:

  • Up-to-date knowledge of machine learning and data analytics tools and techniques
  • Strong knowledge in predictive modeling methodology
  • Experienced at leveraging both structured and unstructured data sources
  • Willingness and ability to learn new technologies on the job
  • Demonstrated ability to communicate complex results to technical and non-technical audiences
  • Strategic, intellectually curious thinker with focus on outcomes
  • Professional image with the ability to form relationships across functions
  • Ability to train more junior analysts regarding day-to-day activities, as necessary
  • Proven ability to lead cross-functional teams
  • Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
  • Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret)
  • Demonstrated Expertise with at least one Data Science environment (R/RStudio, Python, SAS) and at least one database architecture (SQL, NoSQL)
  • Financial Services background preferred

Experience:

  • Master's degree and 5+ years of experience related work experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, scripting languages, and packages, experience with big data analysis tools and techniques, and experience building and deploying predictive models, web scraping, and scalable data pipelines
  • Expert understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling

Education:

  • Master's degree or PhD in computer science, statistics, economics or related fields

Akshit Sisonia - Sr. Technical Recruiter

Email -

LinkedIn -

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