is a leading international mining company with headquarters in Phoenix, Arizona. We operate large, long-lived, geographically diverse assets with significant proven and probable reserves of copper, gold, and molybdenum. The company has a dynamic portfolio of operating, expansion and growth projects in the copper industry. Freeport-McMoRan is one of the world's largest publicly traded copper producers, the world's largest producer of molybdenum and a significant gold producer. We have a long and successful history of conducting our business in a safe, highly efficient and socially-responsible manner. We have the assets, the talent, the drive and the financial strength to provide attractive and rewarding careers of our employees. We encourage you to take the time to explore the opportunity to advance your career at Freeport-McMoRan.
We have the assets, the talent, the drive and the financial strength to provide attractive and rewarding careers of our employees. We encourage you to take the time to explore the opportunity to advance your career at Freeport-McMoRan. Please note:
This position has the possibility of working remotely within 150 miles of Phoenix, Arizona for a percentage of the scheduled work time, as determined by the supervisor. If hired, you will be required to comply with Freeport-McMoRan's requirement of all employees who are working or attending a meeting onsite at a corporate office location, to submit proof that they are fully vaccinated against COVID-19 prior to entry, unless the company has granted them a medical or religious accommodation.
You will be a data science practice leader within a fast-growing Data Science team pursuing a vision of analytics-driven mining at Freeport. You will work in close collaboration with global business leaders, mining operations, subject matter experts, data scientists, and software engineers to develop novel approaches to complex problems. As a practice leader you will develop and lead multiple data science projects within a practice area. Responsibilities will include strategic development, project planning, people development, solution development, and communication planning. Your data analysis, modeling skills, communication, and leadership skills will be an invaluable part of innovation at Freeport.
- Collaborate with business leaders to understand business requirements and manage all aspects of a data science project.
- Develop and Lead a team of Data Science Analysts and Data Scientists in collaboration with other expertise to design and implement complex algorithms and industrialize solutions at scale. Ensure team delivers on commitments by defining clear analytical strategies and principles, maintaining a roadmap for execution, and actively secure its implementation through the scrum process.
- Utilize modern cloud technologies and employ best practices from DevOps/MLOps to manage all aspects of the Solution Development Lifecyle, including but not limited to, code optimization, sustainment, sunset, and obsolescence. Proactively adapting team makeup to increase project velocity.
- Guide problem solving sessions, ensuring alignment to North Star and flexibly seek out R&D initiatives or training opportunities to broaden experience. Provide mentorship and coaching to junior team members.
- Collaborate with a wide range of technical and business experts to craft and deliver a communication strategy that creates broad awareness of data science capabilities and its strategic value to business outcomes
This position requires air travel. In accordance with Freeport-McMoRan's requirement for all employees whose job requires travel by air, if you are hired you will be required to submit proof that you are fully vaccinated against COVID-19 in order to travel by air, unless the company has granted a medical or religious accommodation.
- Bachelor's degree in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline and seven (7) years of relevant work experience, OR
- Master's degree in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline and five (5) years of relevant work experience OR
- Ph.D. in a technical engineering or analytical field (Statistics, Mathematics, etc.) or related discipline and two (2) year of relevant work experience
- Python and SQL Programming Experience
- Expert Practitioner of at least three of the following analytical areas and the ability to articulate theoretical concepts from at least four
- Statistics & Statistical Modeling, including Time-Series Modeling
- Simulation Techniques, including MCMC or an equivalent
- Neural Networks / Deep Learning
- Tree Based Machine Learning Algorithms
- Unsupervised Learning
- Classification techniques, including Support Vector Machines or an equivalent
- Optimization Heuristics
- Text Analytics
- Ability to visualize data utilizing programmatic techniques
- Expert at executing the Data Science development workflow including data manipulation and cleaning, feature engineering, model selection, model training, model validation and model deployment
- Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking to large audiences and storytelling with data.
- Experience developing and leading teams
- Working knowledge of MLOps/DevOps concepts (Version Control, CI/CD, Trunk Based Development/PR Based Development/GIT, Test driven development)
- Working knowledge of Azure Machine Learning Environment
- Working knowledge of Software Engineering and Object Orient Programming Principles
- Working knowledge of Distributed Parallel Processing Environments such as Spark or Snowflake
- Working knowledge of Edge Analytics, embedded systems, or computer vision.
- Working knowledge of Data Architecture, engineering, and ETL teams
- Working knowledge of problem solving/root cause analysis on Production workloads
- Working knowledge of Agile, Scrum, and Kanban
- Strong verbal and written skills in English language.
- Position is in busy, non-smoking office located in downtown Phoenix, AZ
- Location requires mobility in an office environment; each floor is accessible by elevator. Occasionally work will be performed in a mine, outdoor or manufacturing plant setting.
- Must be able to frequently sit, stand and walk.
- Must be able to frequently lift and carry up to 10 pounds.
- Must be able to work in a potentially stressful environment.
- Personal protective equipment is required when performing work in a mine, outdoor, manufacturing or plant environment, including hard hat, hearing protection, safety glasses, safety footwear, and as needed, respirator, rubber steel-toe boots, protective clothing, gloves and any other protective equipment as required.
- Freeport-McMoRan promotes a drug/alcohol-free work environment through the use of mandatory pre-employment drug testing and on-going random drug testing as allowed by applicable state laws
Freeport-McMoRan has reviewed the jobs at its various office and operating sites and determined that many of these jobs require employees to perform essential job functions that pose a direct threat to the safety or health of the employees performing these tasks or others. Accordingly, the Company has designated the following positions as safety-sensitive:
- Site-based positions, or positions which require unescorted access to site-based operational areas, which are held by employees who are required to receive MSHA, OSHA, DOT, HAZWOPER and/or Hazard Recognition Training; or
- Positions which are held by employees who operate equipment, machinery or motor vehicles in furtherance of performing the essential functions of their job duties, including operating motor vehicles while on Company business or travel (for this purpose "motor vehicles" includes Company owned or leased motor vehicles and personal vehicles used by employees in furtherance of Company business or while on Company travel); or
- Positions which Freeport-McMoRan has designated as safety sensitive positions in the applicable job or position description and which upon further review continue to be designated as safety-sensitive based on an individualized assessment of the actual duties performed by a specifically identified employee.
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