Principal Data Scientist

The Principal Data Scientist applies strong expertise in artificial intelligence through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services.
The Principal Data Scientist collaborates with business partners to define the technical problem statement and hypothesis to test; develops efficient and accurate analytical models that mimic business decisions and incorporates them into analytical data products or tools with the support of a cross-functional team.
He/ she is also responsible for defining and implementing DS standards and toolkit within EGA and building and nurturing the Data Science community within and beyond the CoE.
KEY ACCOUNTABILITIES:

Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
Advocate and educate on the value of data-driven decision making focusing on the 'how and why' of solving problems.
Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts, and developers.
Expert in developing data science capability and can advocate the importance of continuous learning to the data science team.
Set as a role model of best practice through demonstration of self-directed learning and set the data science curriculum across the organization.
Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytic data products.
Ensure consistent and high-quality data science standards and tools are deployed and developed within the organization.
Engineer features by using business acumen to find new ways to combine disparate internal and external data sources.
Share passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods, and standards.
Collaborate, coach, and learn with a growing team of experienced Data Scientists.
Provide leadership and direction across a program of multidisciplinary data science projects, managing resources to ensure delivery.
Recognized as a strategic authority with technical expertise in cutting-edge techniques, defining vision across the organization.
Communicate with senior stakeholders and convince them of the strategic value of applying data science.
Stay connected with external sources of ideas through conferences and community engagements.
AUTHORITY/ DECISION MAKING:

Thinking within broadly defined policies, standards, and objectives.
The determination of 'what needs to be done' in applying policies is largely left up to the incumbent who must establish the plan, determine the priorities and prescribe the processes needed to achieve the objectives.
Subject to general direction and broadly defined functional policy objectives.
Actions which will impact other functional or operating areas usually require approval before they may be implemented.
QUALIFICATIONS & SKILLS:

Qualifications
MS or PhD in Data Science, Computer Science, Engineering, Statistics.
Programming languages knowledge, ideally in Python, R, and SQL.
10+ years of relevant experience in a statistical and data science role.
Domain expertise and knowledge in Metal & Mining or Energy or a combination of both industries.
Proficiency working with Data Frames and writing complex SQL queries.
Proficiency with Machine Learning to solve clustering, classification, regression, anomaly detection, simulation, and optimization problems on large-scale data sets.
Proven ability to merge and transform disparate internal & external data sets together to create new features.
Experience of visualizing/presenting data for stakeholders using:
Tableau, R Shiny, Plotly, Power BI, Periscope, Business Objects, D3, ggplot etc.
Strong knowledge of one or more data science or decision science domains (e.g., explainable artificial intelligence, econometrics, deep learning, Natural Language Processing, time series forecasting, deployment, causal inference, uplift modeling, and/or optimization).
Knowledge of distributed computing or NoSQL technologies is a bonus.
Agile/Digital Experience
Experience of working with large data sets relational databases (SQL), simulation/optimization and distributed computing tools (MapReduce, Hadoop, Hive, Spark, MySQL, H20.ai, Cloud AI platforms, containerization etc.) is desired.
Experience with supporting deployment, monitoring, maintenance, and enhancement of models desired.
Individual Skills
Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.
Bias for action, with an ability to deliver outstanding results through task prioritization and time management.
Demonstrated ability to efficiently learn and solve new business domains and problems.
Number sense; healthy skepticism around the validity of data and its inherent biases.
Exemplary organizational skills with attention to detail & accuracy.
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