Senior Data Scientist Resume
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PROFESSIONAL SUMMARY
- Data scientist whose deep technical background allows him to identify, solve, and apply innovative solutions to complex business problems
- Relentless learner who takes initiative to explore and answer big and small questions
- Strategic communicator who uses managing and coaching skills to make technical ideas accessible to a lay audience, to motivate and coordinate teams, and to provide stakeholders wif an effortless experience
TECHNICAL SKILLS
- LinuxWindows
- Python
- TensorFlow
- RSQL
- Tableau
- MATLAB
- MPL MS Office
- Amazon Web Services
- Google Cloud Platform
- Supervised & unsupervised machine learning
- Data validation & analysis
- Data visualizations
- Algorithm design & development
- Deterministic & stochastic optimization
- Modeling
- Project management
- Team management
- Technical report writing
- Written and oral communication
PROFESSIONAL EXPERIENCE
Senior Data Scientist
Confidential
Responsibilities:
- Conducted descriptive analytics on client data in order to provide actionable insight on hiring, retention, and compensation
- Developed descriptive and predictive machine learning models using TensorFlow, XGBoost, and other libraries in order to provide insight on hiring and retention
- Used Tableau and Python libraries to create visualizations of data and machine learning outputs
- Presented machine learning and analytics results to clients’ executive leadership
- Worked independently and wif client teams to source, clean, and validate data
- Utilized REST APIs to integrate HR systems (e.g., Dayforce, Workday) wif existing client systems
- Guided and assisted wif teh implementation of HR systems
- Used Excel and Python to create bespoke tools dat organize, consolidate, and visualize client data
- Created tools to automate teh weekly and periodic reporting of client HR data
Operations Research Analyst Systems
Confidential
Responsibilities:
- Worked wif an internal team to understand constraints and requirements related to clients’ logistics and scheduling problems
- Used constraints and requirements to define model inputs
- Preprocessed input data using supervised and unsupervised machine learning to create additional model inputs
- Built stochastic and deterministic optimization models to represent clients’ logistics and scheduling problems
- Improved existing and developed new optimization algorithms, increasing teh computational efficiency of teh models and allowing for teh creation of more complex ones
- Used cloud and local servers to deploy algorithms at scale, allowing more complex client problems to be solved
- Wrote technical reports detailing modeling steps and procedures
- Managed a team of four programmers to develop new internal and external software dat supported teh models
Operations Research Consultant
Confidential
Responsibilities:
- Collaborated directly wif clients to better understand their logistics and scheduling problems
- Determined client constraints and requirements and defined them as model inputs
- Built models to represent clients’ problems
- Used deterministic and stochastic optimization techniques to solve teh models
- Presented recommended courses of action to clients based on simulation results
Program Director
Confidential
Responsibilities:
- Founded, directed, and coached a rowing program for high school - aged athletes, particularly those from underrepresented populations
- Coached masters sweep and sculling teams, including adaptive teams, at recreational and competitive levels
- Developed annual team budgets, organized and led fundraising campaigns, and tracked team expenses
- Served on teh board of directors as both coach and vice president of operations
- Hired, trained, and evaluated assistant coaches
