TITLE: Data Scientist (Machine Learning)
LOCATION: Houston
TYPE: Direct Hire
SALARY: $170,000 - $185,000
SUMMARY:
The Data Scientist (Machine Learning) will design, develop, implement, maintain, and improve advanced data science initiatives across business units, directly aligning with strategic objectives. This role encompasses transforming innovative ideas into real-world solutions through the application of sophisticated analytical techniques such as machine learning, optimization, and advanced analysis. You will deliver impactful analytical solutions, ensuring these innovations are seamlessly embedded into business operations to drive decision-making, enhance operational efficiency, and foster a culture of continuous improvement and innovation. You will play a significant part in setting the AI & ML agenda, including working with business units to define potential opportunities, and defining standards and best practice for AI & ML.
DUTIES:
- Design, train, and implement machine learning (supervised and unsupervised) algorithms
- Build, deploy, and maintain machine learning algorithms, interface endpoints, and back-end data infrastructure for digital products.
- Perform data mining, exploration, and time series analysis
- Designs machine learning and advanced analytics solutions, algorithms, and cloud architectures needed to satisfy product features and functionality defined by product owner and other stakeholders in a production environment
- Works in all phases of the software development life cycle including functional analysis, development of technical requirements, technical design, prototyping, coding, testing, deployment, data migration, and support
- Assists in integrating subsystems such as data pipelines, AI/ML algorithms, API interfaces into end-user facing products
- Participate in daily scrums, work with Scrum Master and QA Team on projects, and support delivery timelines and priorities
- Organizes and prioritizes individual workload with scrum team through story pointing
- Creates detailed documentation which describes methodology, relevant instructions, and test results
- Finds, analyzes, and fixes bugs and performance problems whenever and wherever they may occur
- May supervise or oversee the work of one or more employees or contractors.
- Carries out responsibilities in accordance with the organization's policies and applicable laws.
- Demonstrated ability to lead and manage data science projects, including, managing workflow and priorities, to ensure timely delivery of projects with high-quality outcomes.
- Proven track record of recruiting, training, and retaining a skilled data science team, identifying talent gaps, and addressing them.
REQUIREMENTS:
- 5 years of experience and proficient in at least one analytical programming language relevant for data science.
- Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI).
- Expertise in advanced analytical techniques (e.g., descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, etc.)
- Experience with Time-Series Forecasting Methods, Regression Models, Clustering/Dimensionality Reduction
- Familiarity with Mixed-Integer-Linear-Programming Algorithms, CPLEX, Gurobi
- Experience with cloud computing environments (AWS, Azure, or GCP) and Data/ML platforms (Databricks, Spark).
- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop.
- Experience in Supervised and Unsupervised Machine Learning including classification, forecasting, anomaly detection, pattern recognition using variety of techniques such as decision trees, regressions, ensemble methods and boosting algorithms.,
- Good understanding of programming best practices, building for re-use and highly automated CI/CD pipelines.
- Proven track record of leading cross-functional teams to successfully deliver complex data-driven projects.
- Excellent problem-solving and analytical skills, with the ability to translate complex technical details into understandable business insights.
- Sees overall 'picture' and alternative approaches and develop vision of what may be possible.
- Strong interpersonal and communication skills, capable of working effectively with and developing trust from both non-technical and technical counterparts to influence key use case & enterprise decisions.
EDUCATION:
- Bachelor's degree in a related discipline and 4 years' experience in a related field.
- Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous.