Lead Data Scientist

$101,400 - $183,300/Yr

Leidos - Reston, VA

Full-time - Senior

Reston, VA

1,001-5,000 employees

Professional, Scientific, and Technical Services

About the position

Leidos is seeking a Lead Data Scientist to join its Corporate Financial Planning & Analysis (FP&A) team. This role involves leading a new data science team focused on enhancing enterprise financial analytics and forecasting. The Lead Data Scientist will collaborate with senior leadership to build a Data & Analytics team within Finance, utilizing statistical models and machine learning to derive insights and support decision-making processes.

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.
• 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.
• Teaches and develops skills of non-technical team members, including those with Finance backgrounds who want to learn more about Data Science/Analytics.

Requirements

• 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 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 and its potential roles in solving business problems.
• Strong experience with Python and fluency in multiple programming languages and statistical analysis tools such as C++, JavaScript, R, SAS, Excel, SQL, MATLAB, SPSS.
• Experience with frequentist statistics and probability including predictive modeling.
• Knowledge of statistical and data mining techniques such as GLM/regression, random forest, boosting, text mining, hierarchical clustering, deep learning, CNN, RNN.
• Experience working with data manipulation, analytic/business insight tools, and data visualization experience.
• Demonstrated experience using statistical and machine learning techniques including supervised and unsupervised learning and natural language processing.

Nice-to-haves

• 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.