Data Scientist I

Job Description

Summary
This position primarily involves work in the Analytics field and working with and supporting EPHD Analysts for all levels and types of analysis which will expand as skills/experience/confidence grow. Will work with our data rationalization team and other Data Scientists (US, AMS and India) to develop a deep understanding of our EPC Model to perform many/varied activities for the team as skills are demonstrated. As experience increases and independent work is started will perform data preparation, data extraction, transfer and loading, data QA & validation, issue/problem identification and resolution, data cleansing and other processing, filter application, reference class development, testing and deployment, verification, smart report visualizations/graphics development, implementation and testing, specification development (spec pkg development and storage/management), descriptive analyses support and analytics charts deve/impl/testing for it, possible predictive modeling/testing in later period once chart dev/impl/test and analysis support type skills are mastered, project/scenario simulation, testing, and interfaces and communications with other groups including information technology, data support, information management/systems, and various project groups, locally and remotely (both in and out of country).

Scope
This role supports the development, testing, implementation, and maintenance of the Fluor Big Data Analytics Environment and System(s). The Data Scientist role takes direction from the Lead Data Scientists and Analyst(s) as well as management in order to assist in the work to design, implement and test various types of statistical analyses and prediction models, including understanding the existing systems, processes, and the investigation, development, testing, quality inspection, and validation of new Analytics Charts, system components, tools, and data, when there are additions, changes or maintenance requirements. The Data Scientist role requires the development of a deep understanding of the data, processes and systems, to set up various systems of analysis and their smart graphics to enable knowledge, insights/indicators to be extracted as information from the data input, its triangulation, and presented to the users in various forms. This includes real time data manipulation and chart development at times when working with the analysts and project teams, and with the EPHD sandbox environment as well with R Shiny and R Studio (no called Posit). The data may be obtained, for example, from structured and/or unstructured data formats and a wide variety of sources (including new investigation with new data sources). This position requires the candidate to work in a highly collaborative environment with other data scientists, analysts, the EPHD Manila data repository team, project team personnel as may be directed, some key vendors, and company management. Being a data scientist engrossed in the support of the entire end to end data management process all culminates into a role to provide clear, easy to use, access, and understand the results, observations, and findings fashioned into a story for EPHD Analytics communications which then enables further deep investigation by the project teams (management team leaders including for example project controls, project planners, project schedulers, supply chain, engineering mgmt. and construction mgmt), ultimately to drive project execution performance results for the company.

This is an entry level position, in which the candidate for this role would come in without much knowledge or understanding of the engineering, procurement, and construction industry, and would be lead by the Data Scientist leaders and EPHD Analysts to grow and thrive in this position and to become a leader in the candidate's own right.

Basic Job Requirements

Degree in Mathematics/Statistics with courses in data science, participating in projects, and internship(s), regarding Data Analytics, good to have some taste of statistically accurate predictive modeling, and statistical machine learning, but data cleansing, data preparation, and deep chart development and work with databases will be more important when starting out.
Graduate from a well-ranked university, with high GPA;
If possible demonstrable internship/industry experience involving practical applications of statistical, mathematical, predictive modeling, machine learning, deep learning knowledge, as a part of a Bachelor's of Science if that was part of the content of the degree, and certainly if this experience was obtained as a part of your Master's of Science degree. Please supply such work experience and references.
Highly Valued is a strong knowledge and experience using programming languages such as R, Python, SQL, Shiny (Posit), Plotly, Version control (GIT, TFS (DevOPs), Java, JavaScript, JSON and similar products, with ability to pick up new programming languages as may be needed (including a demonstration of how you would pick up R if you do not have it as a part of your degree).
Some familiarity working with database systems including e.g., SQL, and identify any experience obtained with respect to other db systems like Mongo etc.
Multi time zone support required, must be ok with working early hours (or off normal work day hours) to work and coordinate with others in Asia, Europe, India, Philippines for example and with other US Time Zones like ET, MT, and PT when required.

Principal Job Duties & Responsibilities
Improve and/or develop R/python and some SQL related to DB queries and algorithms for data extraction, transformation, and cleaning of the structured and unstructured data from Fluor project execution & business tools /systems;
Improve and/or develop and support the data preparation, R, Python, Java and LWRS (Fluor unique learned on the job) code for smart graphics visualizations and analytics charts (for descriptive, predictive and operational requirements from mgmt and analyst teams) in the sandbox of R studio and R shiny (now Posit) and working with IT to move those charts through the formal dev, QA/Test environments and then into validation and production environments;
Integrate data sets; Develop or program databases and query them to retrieve data to perform statistical analysis and to create reference class cohorts of data as may be required;
Use statistical analysis and programming to understand and work around possible data limitations
Brainstorm with functional experts in performing exploratory and "Ad Hoc" data analytics development to diagnose the execution issues in the large hundreds of millions and mega multi-billion-dollar capital projects, and develop the related visualizations required for understanding the results, using tools such as R and others and its visualization packages such as gg plot, plotly shiny apps, LWRS, etc.
Responsible for development of analytics charts from start to end including specification package development review/explanation, Data Preparation, visualization development using R, Java Script, Plotly, testing and review with analysts. The ability to write JSON objects to transfer data and JavaScript code to UI, and maintaining code using Git version control are valued assets. The use of POSIT software version management and library mgmt. as well as security package administration, and of the use of tools like TFS (now rebranded to "DevOps"),

Other Job Requirements

Ability to work in a fast-paced multi-disciplinary environment. Strong sense of urgency and high work ethic. High collaboration skills. Ability to multi-task. Self motivated, self started, not afraid to ask questions and dig in. Ok not to know something, but need to see the ability to try to learn and then ask for help, absorb and become independent over time. Build and nurture solid relationships within EPHD Teams and all the teams we work with. Be able to take direction and use your own creativity in solving problems. Show work efforts along the way and confirm direction and objectives.
Natural curiosity to go beneath the surface of a problem, and to write calculations, algorithms, analytics to uncover and raise root causes to problems. Possess the patience to find the unknown in massive data sets and develop algorithms to unlayer issues with experts guiding and also through some trial-and-error.
Strong written and verbal communication skills. Thrives in a team environment. Works well with others. Highly collaborative. Flexible to support multiple time zone teammates.
As one grows in their capabilities some data scientists will work on, or with other data scientists on, the development of new prediction models or enhance & maintain existing prediction models, including assessing and resolving for any "drift" along with other issues and problems, to ensure we maintain high confidence when predicting the future outcomes of capital projects using machine learning techniques e.g., Random Forest, Naive Bayes, SVM, Elastic Net, and XGBoost.
Perform QA testing for various developments by the EPHD team and by the IT team/vendors for end to end development, the EPHD UI / prediction models / Chart development work, and participate as requested in peer review to Fluor data science colleagues
Work autonomously and in a highly collaborative team environment (sometimes as support and sometimes as lead as you grow into various roles and take on more responsibility over time).
Be highly motivated and a self starter. Ask questions. Love to learn and grow and provide support as a service to teammates and projects.
Be a good communicator, be engaged with your peers and management, ask questions and get involved when possible in the process of analysis to learn and understand what is important and why.

Notice to Candidates:

Background checks are carried out as part of any conditional offer made, including (but not limited to & role dependent) education, professional registration, employment, references, passport verifications and Global Watchlist screening.

Benefits

Fluor is proud to offer a comprehensive benefits package designed to promote employee health, wellness, and financial security. Our offerings include medical, dental and vision plans, EAP, disability coverage, life insurance, AD&D, voluntary benefit plans, 401(k) with a company match, paid time off (personal, bereavement, sick, holidays) for salaried employees, paid sick leave per state requirement for craft employees, parental leave, and training and development courses.