Senior Data Scientist

Description

Job ID 5598

US working hours

Why Ness

We know that people are our greatest asset. Our staff’s professionalism, innovation, teamwork, and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee, you will be working on products and platforms for some of the most innovative software companies in the world.

You’ll gain knowledge working alongside other highly skilled professionals that will help accelerate your career progression.

You’ll also benefit from an array of advantages like access to trainings and certifications, bonuses, and aids, socializing activities and attractive compensation.

Requirements And Responsibilities

The Network Data Scientist role is pivotal in developing and delivering predictive and inferential models to improve business performance at Zayo. Responsibilities include leading data science and machine learning-based programs and initiatives, as well as managing model life cycles.

This role requires a blend of deep technical expertise in statistical and machine learning models, code development, innovative thinking, and strong communication skills to collaborate with stakeholders in the operations organization.

You will play a crucial role in driving data-driven decision-making and innovation, ultimately contributing to the organization's success by applying statistics and ML techniques to data to solve business problems and optimize operations. Strong analytical, problem-solving, communication, and interpersonal skills are essential for success in this role.

What You’ll Do

• Identify data requirements.
• Help business teams make decisions, answer questions, and solve problems more efficiently and effectively using data-driven, fact-based, and model-based approaches.
• Design, engineer, develop, test, validate, deploy to production, operate, and support DS models to solve predictive problems like time to failure of equipment, future resource usage, and resolve inventory discrepancies between multiple systems.
• Design engineer, develop, test, validate and deploy to production, operate, and support DS models to solve complex multi-variable problems like routing cost analysis, inventory quality analysis between multiple data sets, and field repair time optimization.
• Deliver business value through cost reduction, avoidance, and optimization of processes.
• Contribute to network data strategy and process improvement efforts with a focus on innovation through data science and machine learning.
• Collaborate with internal and external stakeholders to manage project status and any blockers.
• This role requires US Working hours (14:00 - 23:00 Romanian time).

What You’ll Bring

• Bachelor’s or Master’s in Data Science, Computer Science, Mathematics, Statistics, or related fields.
• 5+ years of data scientist or similar role involving data extraction, analysis, and statistical modeling.
• 5+ years experience with Python and SQL, writing complex and efficient queries.
• 3+ years working in environments with multiple and distributed data sources.
• 3+ years working in both cloud and on-premise computing environments.
• Experience and proficiency in Excel.
• Experience with time series forecasting, regression models (LR, XGBoost, SVR, prophet etc. ) and deep learning (NN, CNN, LSTM etc.)
• Experience with data manipulation libraries like (Pandas, Polars etc.)
• Excellent interpersonal skills, with the ability to effectively communicate technical work to non-technical audiences.
• Forward-thinking, anticipates and prevents problems and roadblocks before they occur.
• Proven attention to detail, critical thinking, and the ability to work both independently and collaboratively within a cross-functional team.
• Proven self-starter who can work autonomously but is also comfortable with a team lead role on a project.
• Ability to plan, prioritize, and organize effectively and work under pressure deadlines.

Other Preferred Qualifications

• Familiarity with CI/CD pipelines for machine learning and MLOps practices.
• Experience with working with DS problems in inventory.
• Background in a high-growth or tech-driven industry.
• Experience on a DS/ML Automation platform like Dataiku.

Not checking every single requirement?

If this role sounds good to you, even if you don’t meet every single bullet point in the job description, we encourage you to apply anyway. For most of the candidates that applied, we found a role that was a very good fit with their skills.

Let’s meet and you may just be the right candidate for one of our roles.

At Ness Digital Engineering we are willing to build a work culture that is based on diversification, inclusion, and authenticity.