Lead Data Scientist

Description

Leidos' Corporate Financial Planning & Analysis (FP&A) team is looking for an experienced Data Scientist with an entrepreneur's mindset to support a new data science team working on projects to improve our Enterprise financial analytics and forecasting.The position will collaborate with the SVP and VP of FP&A in building a Data & Analytics team within Finance as well as lead new team. The position is funded and an immediate fill opportunity.

The Lead Data Scientist will be expected to build statistical models, test hypotheses, interpret, summarize, visualize, and succinctly report on data findings. The Scientist will leverage automation and machine learning to manage data, predict scenarios and make recommendations. The data scientist will partner with business and operational leaders to provide an impact by leveraging data and analytical tools, strategic thinking, and hypothesis-based analysis on machine learning (ML)-based projects. The data scientist is responsible for modeling complex business problems through statistical, algorithmic, mining, and visualization techniques. Further, they will support senior leadership by creating business insights, reports, and analyses to aid in the decision-making process.

Primary Responsibilities:

• Translates business needs into analytics/reporting requirements to support executive decisions and workflows with required information
• Performs large-scale experimentation and builds data-driven models to answer business questions
• Proactively mines data warehouses to identify trends and patterns and generates insights for business units and senior leadership
• Performs large-scale experimentation to identify hidden relationships between variables in large datasets
• Researches and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient
• Designs and conducts data analyses with the highest standard of rigor and scientific accuracy; this includes study design, methodology, algorithms, and statistical modeling
• Teach and develop skills of non-technical team members (team will include members with Finance backgrounds who want to learn more about Data Science/Analytics)

Required Qualifications:

• Bachelor's degree and 8+ years of relevant experience in data analytics, including 6+ years of experience in successfully launching, planning, and executing data science projects, including statistical analysis, data engineering, and data visualization
• Prior experience in Finance, FP&A, Accounting or Economics (understand Income, Balance Sheet, and Cash Flow Statements) is required
• Ability to communicate complex projects, models, and results to a diverse audience with a wide range of understanding/technical backgrounds
• Ability to lead a mixed team of Data Scientists and Finance professionals
• Strong understanding of AI, its potential roles in solving business problems, and the future trajectory of generative AI models
• Strong experience with Python as well as fluency in multiple programming languages and statistical analysis tools such as C++, JavaScript, R, SAS, Excel, SQL, MATLAB, SPSS
• Experience / familiarity with frequentist statistics and probability including predicative modeling
• Knowledge of statistical and data mining techniques such as generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN)
• Experience working with data manipulation, analytic/business insight tools, and data visualization experience
• Experience constructing and performing complex database search queries
• Ability to work in diverse, cross-functional teams in a dynamic business environment
• Demonstrated experience using statistical and machine learning techniques including supervised and unsupervised learning and natural language processing
• Proven experience in conducting statistical analysis and building models with advanced scripting languages

Preferred Qualifications:

• Experience leading projects that apply ML and data science to business functions
• Specialization in text analytics, image recognition, graph analysis, or other specialized ML techniques, such as deep learning, is preferred
• Candidates will ideally have a specialization in ML or AI

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.