Senior Data Scientist| Analytics| R & R Shiny Mandatory

Job Description

About Argus: Argusis the leading independent provider of market intelligence to the global energy and commodity markets. We offer essential price assessments, news, analytics, consulting services, data science tools and industry conferences to illuminate complex and opaque commodity markets. Headquartered in London with over 1,400 staff,Argusis an independent media organisation with 30 offices in the worlds principal commodity trading hubs. Companies, trading firms and governments in 160 countries around the world trustArgusdata to make decisions, analyse situations, manage risk, facilitate trading and for long-term planning.Argusprices are used as trusted benchmarks around the world for pricing transportation, commodities and energy. Founded in 1970,Argusremains a privately held UK-registered company owned by employee shareholders and global growth equity firm General Atlantic. ArgusMedia is committed to ensuring career and personal growth for all its staff and provides extensive training and career development opportunities, as well as participation in employee-led initiatives, including a women’s network. Our core values are Excellence, Integrity, Partnership and Inclusivity. What will you be doing? An exciting opportunity has arisen for a senior data scientist with expertise in R, R-Shiny and SQL to join our growing Data Science team in Mumbai. You will work closely with our Head of Data Science India, and our global team to support the development of new products for analytics with a particular focus on Petrochemicals. You will be responsible for building impactful data science solutions for business use cases, conducting research on large complex data sets to uncover meaningful patterns in data, employing mathematical and computational techniques to clean, manipulate, organise and model data into actionable insights and results. Apply novel data science, machine learning and statistical techniques to provide an unbiased and quantitative solution to critical business problems. Develop, structure and investigate your ideas by constructing hypotheses, testing them rigorously, conducting analyses, creating user prototypes, facilitating UAT, and finally presenting recommendations for improvement to current business processes. Build user-focused data science/analytics products based on novel business use cases for internal as well as external stakeholders. Develop and maintain models with a focus on commodity prices dynamics. Write production-level code (clean, optimised and well-documented code) Communicate findings timely through impressive visuals and insightful statistics. What we’re looking for? Degree in mathematics, finance, statistics, engineering, computer science or related field. Experience with statistics, regression, time series and econometrics is preferred. 4+ years Hands-on experience working in R and R-Shiny, good command over SQL with a passion for open-source solutions 2+ years’ experience in project management & team management Robust Knowledge of Data Structures & Algorithms, APIs, ETL processes, testing methodologies, cloud technologies (AWS). Experience with designing and building exploratory data analysis and data visualisation Solution-oriented mindset and self-directed. Experience in using version control software, project management solutions Believe in the following Argus values: Passion, Integrity, Excellence and Results. What’s in it for you: Competitive salary Hybrid Working Policy (3 days in Mumbai office/ 2 days WFH once fully inducted) Group healthcare scheme 18 days annual leave 8 days of casual leave Extensive internal and external training Hours: This is a full-time position operating under a hybrid model, with three days in the office and up to two days working remotely. The team supports Argus’ key business processes every day, as such you will be required to work on a shift-based rota with other members of the team supporting the business until 8pm. Typically support hours run from 11pm to 8pm with each member of the team participating up to 2/3 times a week.