Description
The Staff Data Scientist will translate business problems and opportunities into data science projects. Conduct data analysis and build machine learning models for internal and client-facing applications. Present findings to key stakeholders. Deploy production models. This position will work closely with software development to provide valuable insight to improve business operations.
RESPONSIBILITIES
- Meet with business leaders to understand business challenges and opportunities, and then frame these as data science problems
- Identify data sources and evaluate suitability for use in analysis and modeling
- Manage complex projects by demonstrating scope of data science projects by defining and planning steps
- Extract data from enterprise systems and clean the data for analysis and modeling
- Conduct analysis to derive insights from data
- Develop visualizations of analytics and models for communicating findings
- Build, test, and validate predictive models
- Put models into production
- Present insights to key business stakeholders
- Mentor junior data scientists
- Identify opportunities to collect data from new sources or improve existing processes to allow for better analysis and modeling
- Implements new or enhanced software designed to access and handle data more efficiently.
- Identifies creative solutions to challenging data science problems, determines project requirements and model requirements, and delivers a solution through the lifecycle to the production environment.
Qualifications
Education/Certification:
- Bachelor's Degree in Computer Science, Data Science, Business Analytics or similar quantitative field
Experience:
- 5+ years in a data scientist role
Skills/Abilities:
- R and/or Python; SQL; statistical analysis and modeling, including linear and generalized linear models; time series analysis and forecasting; machine learning models such as random forests, XGBoost, and SVM; Spark (in Scala or from R or Python)
- Natural language processing, including topic modeling, intent & entity extraction, and/or building domain-specific language models.
- Demonstrate a high level of autonomy and ability to produce high quality work with minimal guidance.
- Demonstrated ability to communicate data science findings and recommendations to technical and non-technical audiences, including senior and executive leadership.
- Experience monitoring models in production.
- Experience in data mining
- Understanding of machine learning
- Strong analytical skills and business acumen
PREFERRED QUALIFICATIONS
Education/Certification:
- Master's degree in Computer Science, Data Science, Business Analytics, or similar quantitative field.
Experience:
- 7+ years in a data scientist role
Skills/Abilities:
- Neural networks, including CNN and RNN architectures
- Building production APIs in Flask, FastAPI or similar frameworks
- Experience deploying models in Docker containers on Kubernetes
- Experience deploying models on-device for iOS and Android
Paycom is interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas for this position.
Paycom is an equal opportunity employer and prohibits discrimination and harassment of any kind. Paycom makes employment decisions on the basis of business needs, job requirements, individual qualifications and merit. Paycom wants to have the best available people in every job. Therefore, Paycom does not permit its employees to harass, discriminate or retaliate against other employees or applicants because of race, color, religion, sex, sexual orientation, gender identity, pregnancy, national origin, military and veteran status, age, physical or mental disability, genetic characteristic, reproductive health decisions, family or parental status or any other consideration made unlawful by applicable laws. Equal employment opportunity will be extended to all persons in all aspects of the employer-employee relationship. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation benefits, and separation of employment. The Human Resources Department has overall responsibility for this policy and maintains reporting and monitoring procedures. Any questions or concerns should be referred to the Human Resources Department. ****To learn more about Paycom's affirmative action policy, equal employment opportunity, or to request an accommodation - Click on the link to find more information: paycom.com/careers/eeoc
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