Full Description and Link to Apply

LOCATION
Enact Headquarters, Raleigh, NC – Hybrid Schedule

YOUR RESPONSIBILITIES

Design and develop ML frameworks and deep learning applications and systems.

Extend and enrich existing ML frameworks and libraries.

Construct optimized data pipelines to feed ML models.

Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.

Research, experiment with, and implement suitable ML operational processes and tools.

Train and re-train ML systems and models as and when necessary.

Perform statistical analysis and fine-tune models using test results.

Explore and visualize data for better understanding

Identify differences in data distribution that could impact model performance when deploying it in real-world scenarios.

Stay up to date with developments in the machine learning and AI space to educate and advise data scientists to improve their day-to-day ML operations.

YOUR QUALIFICATIONS

Bachelor’s Degree in Computer Science, Mathematics, Physics, or other technical fields.

3+ years of hands-on experience with data modeling, developing analytical data sets and software architecture

3+ years working with various Machine Learning libraries and packages like Scikit learn, Theano, TensorFlow, Matplotlib, Caffe, etc.

Programming experience in Python, SQL 

Working knowledge AWS ML, compute, and storage products.

Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc.

Strong written and verbal communication skills. 

Intrinsically motivated to learn and grow.

Proven collaboration skills.

Excellent time management and organizational skills.

Strong analytical skills with high attention to detail and accuracy. Demonstrated ability to successfully collaborate with business stakeholders.

Working knowledge of forecasting techniques, supervised and unsupervised predictive models.

PREFERRED QUALIFICATIONS

Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc.

Experience working in risk modeling and analytics, and or in financial services companies.

Master's degree in machine learning, neural networks, deep learning or related fields.

Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, regression & forecasting techniques, etc.).