Senior Data Scientist
Sage
San Jose
hace 2 días

People make Sage great. From our colleagues delivering ground-breaking solutions to the customers who use them : people have helped us grow for more than thirty years, and people are driving our future as a great SaaS company.

We're writing our next chapter. Be part of it!

At Sage, we recognize that the world of work has rapidly shifted over the last few years, particularly how we work. That is why we have committed to working in a hybrid way going forward.

Human connection is an essential ingredient of the 4 principles that make up our Flexible Human Work hybrid framework and we want to be transparent in what that looks like when you join our Sage family.

On one hand, our offices will continue to play an important role in our future and serve as a place for spontaneous conversations, connection, collaboration as well as focused time.

On the other hand, we have learned to reimagine where and when we work and to unlock that flexibility and innovation for our colleagues offering them the opportunity to work flex across their home, Sage offices or customer sites.

We invite you to join us and help us write our next chapter. Follow us on our social media sites to join in conversations about open positions and company news! #lifeatsage #sagecareers.

If you would like support with your application (or require any adjustments) please contact us at for assistance. All qualified applicants will be thoughtfully considered and never discriminated against based on their race, color, age, religion, sexual orientation, gender identity, national origin, disability or veteran status.

EOE AA / M / F / Vet / Disability Sage Software is an Equal Opportunity Employer. We comply with the laws set forth in the Equal Employment Opportunity in The Law poster :

Who we are :

Sage Artificial Intelligence Labs "SAIL" is a nimble team within Sage building the future of cloud business management by using artificial intelligence to turbocharge our users' productivity.

The SAIL team builds capabilities to help businesses make better decisions through data-powered insights.

As a part of our team, you will be crafting machine learning solutions to help steer the direction of the entire company’s Data Science and Machine Learning effort.

You will have chances to innovate, contribute and make an impact on the rapidly growing FinTech industry.

You will have overall technical ownership of designing, developing, delivering, and maintaining high quality machine learning solutions that contribute to the success of Sage and contributes intelligence to its products.

If you share our excitement for machine learning, value a culture of continuous improvement and learning and are excited about working with cutting edge technologies, apply today!

Qualifications :

  • Deep understanding of statistical and machine learning foundations
  • Experience designing, developing and scaling machine learning
  • 4+ years industry experience training and shipping production machine learning models.
  • Proficiency with Python, R, Pandas and ML frameworks such as scikit-learn, PyTorch, TensorFlow etc
  • Experience with NLP and applying ML in the Accounting / Finance domain a plus
  • Deep experience with : logistic regression, gradient descent, regularization, cross-validation, overfitting, bias, variance, eigenvectors, sampling, latency, computational complexity, sparse matrices.
  • Preferred Qualifications :

    MS in Computer Science, Electrical Engineering, Statistics, Physics, or similar quantitative fields.

    Experience with NLP and applying ML in the Accounting / Finance domain a plus

    Experience wrangling data, writing SQL queries and basic scripting.

    Deep experience with : logistic regression, gradient descent, regularization, cross-validation, overfitting, bias, variance, eigenvectors, sampling, latency, computational complexity, sparse matrices.

    You may be a fit for this role if you :

    You’re comfortable investigating open-ended problems and coming up with concrete approaches to solve them.

    You don't only use machine learning models but can implement many machine learning and statistical learning models from scratch and know when / how to apply them to real world noisy data.

    You’re a deeply curious person and eager to learn and grow.

    You often think about applications of machine learning in your personal life

    What's it like to work here

    You will have an opportunity to work in an environment where Data Science is central to what we do. The products we build are breaking new ground, and we have a focus on providing the best environment to allow you to do what you do best - solve problems, collaborate with your team and push first class software.

    Our distributed team is spread across multiple continents, we promote an open diverse environment, encourage contributions to open-source software and invest heavily in our staff.

    Our team is talented, capable and inclusive. We know that great things can only be done with great teams and look forward to continuing this direction.

    Key Responsibilities

    Building, experimenting, training, tuning, and shipping machine learning models in the areas of : classification, clustering, time-series modeling and forecasting.

    Define and develop metrics and KPIs to identify and track success

    Working with product managers and engineers to translate product / business problems into tractable machine learning problems and drive the ideas into production using machine leaning

    Collaborate with architects and engineers to deliver ML solution and ship code to production

    Take an active role within the team to contribute to its objectives and key results (OKRs) and to the wider AI strategy

    Adopt a pragmatic and innovative approach in a lean, agile environment

    Presenting findings, results, and performance metrics to stakeholders.

    Do you love where you work? WE do!

    Who is Sage?

    How we make a difference :

    Champion of Business Builders :

    Life at Sage :

    Our comprehensive total rewards program included :

  • Extended health, dental and vision coverage
  • On-going training and professional development
  • 21 days paid time off from the start
  • Paid 5 days to volunteer through our Sage Foundation
  • Matching Retirement contributions
  • And, so much more
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