Data Scientist - Senior

Genesis10
Darlington
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Genesis10 is seeking a Data Scientist: III (Senior) for a hybrid 3-month contract to hire position with a leading client in Columbus, OH.


Compensation: $65 per hour W2; Conversion salary $105k with a 15% bonus


Job Description

As we advance our data science and analytics capabilities, we want experts in modeling complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The Senior Data Scientist contributes to building and developing the organization's data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision‑making processes.


Responsibilities

  • Performs advanced analytics methods to extract value from business data
  • 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
  • Determines requirements that will be used to train and evolve deep learning models and algorithms
  • Articulates a vision and roadmap for the exploitation of data as a valued corporate asset
  • Influences product teams through presentation of data‑based recommendations
  • Evangelizes best practices to analytics and products teams
  • Owns the entire model development process, from identifying the business requirements, data sourcing, model fitting, presenting results, and production scoring

Requirements

  • 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
  • Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
  • Strategic, intellectually curious thinker with focus on outcomes
  • Professional image with the ability to form relationships across functions
  • Strong experience with R/RStudio, Python, SAS, SQL, NoSQL
  • Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker)
  • Strong experience with machine learning environments (e.g., TensorFlow, scikit‑learn, caret)
  • Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non‑linear regression, hierarchical, mixed models/multi‑level modeling
  • Financial Services background preferred
  • 1-3 years' work and/or educational experience in machine learning or cloud computing, experience using statistics and machine learning to solve complex business problems, experience conducting statistical analysis with advanced statistical software, experience scripting languages, and packages, experience building and deploying predictive models, experience web scraping, and scalable data pipelines and experience with big data analysis tools and techniques.
  • Master's degree in computer science, statistics, economics or related fields

Benefits

  • Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years.
  • The opportunity to have a career‑home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years.
  • Access to an experienced, caring recruiting team (more than 7 years of experience, on average.)
  • Behavioral Health Platform
  • Medical, Dental, Vision
  • Health Savings Account
  • Voluntary Hospital Indemnity (Critical Illness & Accident)
  • Voluntary Term Life Insurance
  • 401K
  • Sick Pay (for applicable states/municipalities)
  • Commuter Benefits (Dallas, NYC, SF)

Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.