Principal Data Scientist: MS Azure l SQL l R/Python l Databricks l Spark l Containers l Git l Building effective CI/CD pipelines l PowerBI, Web Frameworks

SUMMARY:
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POSITION INFO:

Principal Data Scientist: MS Azure l SQL l R/Python l Databricks l Spark l Containers l Git l Building effective CI/CD pipelines l PowerBI, Web Frameworks

Reports to: Head Energy Digitalization

This invitation is for a well-qualified and experienced candidate to take feel free to explore unique solutions and try fresh ideas, through a customer-centric approach that will enable Client’s strategic go-to-market aspirations in providing sustainable value to our customers.

The ideal candidate will be confident with statistics and advanced data science methodologies to realize the full potential from large datasets, will have a creative and entrepreneurial mindset with a natural curiosity to problem-solve and be able to explain concepts and results to a non-technical audience. You will be provided the autonomy to manage your own projects whilst enjoying the benefits of remote work.

You will have industry-leading toolsets at your disposal; your experience in the Microsoft Azure platform is preferred. The strategic direction set by Client is compelling and presents an exciting opportunity for highly experienced and self-motivated data scientists who are keen to showcase their skills and join us on this epic journey.

Client has unique set of benefits that an employee receives in return for the skills, capabilities, and experience they bring to a company. It also supports learning and development culture and remains one of the top preferred employers in the country with global footprints spurning many decades.

Short Description / Purpose of Job

The Principal Data Scientist is responsible for preparing and analyzing large data sets to apply appropriate data science techniques (statistics / simulation / optimization / machine learning) to drive predictive and prescriptive intelligence for business applications.

The Principal Data Scientist will be responsible for the design, engineering, development, operationalization, and modification of complex and/or specialized data science products in accordance with sound analytical principles and standards to drive critical value-adding business decisions.

The Principal Data Scientist will forge strong relationships and partnerships with key stakeholders to understand business needs; develop data science products in a way that maximizes user buy-in while recognizing and capitalizing on new improvement opportunities to extract business value.

He/she will lead research and development efforts in the advancement of new data science techniques and and/or tools for relevant application in the Client Energy business.

In addition, the principal data scientist is a subject matter expert and will lead own projects as well as provide support to and mentor other data scientists in the team.

Recruitment Description/ Key Accountabilities

Translate business questions and opportunities into specific quantitative questions that can be answered with available data using appropriate data science techniques (statistics/ simulation/ optimization/ machine learning).

Define, apply, and update Data Science best practices and standards.

Ensure that solutions are sustainable and adequately packaged for support handover.

Peer review other data scientists' work to identify possible areas for improvement of efficiency, effectiveness to ensure and improve the quality and accuracy of the data science products.

Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.

Actively seek customers where support could be offered and proactively identify real business needs.

Research trends in data science tools and techniques for continuous improvement and lead relevant piloting work to test and implement these tools/techniques.

Contribute to the data science community as the subject matter lead on specific topics.

Formal Education

Master's degree ideally in Statistics / Mathematics / Data Science / Operations Research / Engineering. PhD in one of the above fields will be advantageous.

Min Experience

• At least 13 years of applied experience using advanced analytics, statistical methods, and data science.
• Fluency in computer programming and data structures, with expert coding capability in R/Python and SQL.
• Applied data science delivery in any of the following areas: retail / customer loyalty, price and cost optimization / inventory optimization / sales and operations planning / digital twins will be preferred.
• Experience in Agile project delivery is required.
• Demonstrated thought leadership in the field of data science.
• Applied experience in deep learning techniques (e.g., NLP, computer vision, etc.) is preferred, but not essential.
• Good presentation and communication skills with a knack for explaining complex analytical concepts to people from other fields.
• At least 4 years’ experience in any of the following: distributed computing, Databricks, Spark, containers, Git, and building effective CI/CD pipelines, PowerBI, web
• Azure certifications are preferred.

Competencies

Analytics: The systematic computational analysis of data or statistics

Collaboration: The action of working with someone to produce something

Critical reasoning: The action of critically thinking about something in a logical, sensible way and taking all factors into consideration.

Data Management: Knowledgeable of the theory, purpose, architecture and design of the management, administration, and relationships of the organization's data.

Execution capability: The underlying ability to execute a strategy/project or day to day work Problem Solving: Is a step-by-step process of defining a problem, searching for information, and testing a series of solutions until the problem is solved. In involves critical thinking, analysis, and persistence.

Self-Mastery: Takes accountability for driving own growth through developing self-awareness, reflecting, seeking feedback and self-correcting

Tech Savvy: Knowledge of the Information Technology Industry including trends, emerging technology, best practices, competition, regulations, and legislation.

Communication will only be with shortlisted candidates: email me for a skills matrix jino.

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