principal data scientist

Job description:

JOB PURPOSE:

The Principal Data Scientist applies strong expertise in artificial intelligence through 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 to define and implement DS standards and toolkit within EGA, and build and nurture 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. knows how to develop data science capability across the wider organisation and in industry. Sets as a role model of best practice through demonstration of his own self-directed learning. You set the data science curriculum across the organisation.
• 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 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
• provides leadership and direction across a programme of multidisciplinary data science projects, managing resources to ensure delivery.
• Recognised as a strategic authority with technical expertise in cutting-edge techniques, defining vision across the organisation
• Communicates 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 polices 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

Minimum Experience and Domain knowledge

• 10+ years’ of relevant experience in a statistical and data science role
• Should have Domain expertise and knowledge in Metal & Mining or Energy or a combination of both industries and can communicate the business benefit of data science products, championing and governing these across the organisation. Communicates relevant, compelling stories in the most appropriate medium and ensures that data governance and data ethics are embedded in organisational strategy. Expert in aligning data science priorities with wider organisational objectives - for example, budget.
• Practices applied maths, statistics, and scientific practices, knows how to develop deeper expertise on a narrower range of specialisms and can start to apply emerging theory to practical situations.
• 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.
• Practices different Programming languages and knows how to develop, code, test, correct and document simple programs or scripts part of a multidisciplinary team. Knowledge of additional programming languages is a plus (C++, Java, SPSS, SAS, Scala)
• 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 modelling, and/or optimization)
• Expert working with data engineers to map, produce, transform and test new data feeds for data owners and consumers, selecting the most appropriate tools and technologies. Leads ad hoc data exploration in a wide variety of data serialisation and storage formats, from across the business.
• Understands and can help teams apply a range of techniques to analyse data and provide insight across the product life cycle (data science). Proactive and can present compelling findings that inform wider decisions and applies innovative approaches to resolve problems.
• Knowledge of distributed computing or NoSQL technologies is a bonus
• Experience in automation & control system and training in similar fields is valued.

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 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 validity of data and its inherent biases

Mindset & Behaviors

• Intellectual curiosity to understand and answer questions
• Intellectual humility to leverage the expertise of others
• Exemplary organizational skills with attention to detail & accuracy
• Ability to coach, mentor, and collaborate with squad members