Work along with other data scientists and data engineers to support development and maintenance of products that generate key insights on industry trend by applying machine learning and statistical techniques on proprietary and open data sources
Work alongside Product managers, Industry Analysts and Technology experts to develop and deliver the product in accordance with customer requirements and agreed timeline
Work as an Individual Contributor and should be able to manage a team as well
Participate in complex analytical projects and apply data engineering techniques to support new or existing data products
Support the team or management by producing quick-turnaround analysis, model development, and quality assurance for product development, consulting projects, and client presentations
Gather knowledge about the Maritime industry and its interrelationship with various economic and policy decision
Work closely with the research team and product management team to take their inputs and develop a product
Mentor junior team members on various algorithms, tools and techniques in the world of data science
Requirements
10+ years work experience in developing products/services using Data Science and Analytics
10+ years of industrial/research experience in a Data Science/Engineering Team
2-3 years of experience in working in time series forecasting
2+ years of experience in working with cloud technologies AWS/Dataricks
1+ years of experience in implementing LLMs for analytics products/services
5+ years of experience working with Big Data tools (Spark, PySpark, Cassandra, MongoDB etc.)
Experience in creating docker containers
Experience working on end-to-end analytics project from requirements analysis till deployment of project
Ability to perform complex data analysis and statistical modelling in R/Python and/or Spark
Knowledge of RDBMS concepts and experience working with SQL
Understanding of data visualization principles and experience with data visualization tools such as Tableau
Master’s degree in a quantitative discipline (Computer Science, Mathematics, Econometrics, Engineering, Data Science)
In-depth knowledge of forecasting concepts such as S/ARIMA/X and good knowledge on implementing forecasting packages in R and Python
Excellent knowledge of Statistics, Machine Learning algorithms, Deep Neural Networks and Data Mining
Beneficial: Experience working with geo-spatial data and/or unstructured data at scale
Beneficial: Experience in other statistical programming languages like SPSS, Eviews etc.
Beneficial: Experience in working in Maritime Industry
Good logical thinking and problem-solving skills
Good communication skills and ability to confidently present technical solutions to stakeholders
Great teamwork and ability to connect with people and build strong professional relationship
Benefits
Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries
Data Scientist focusing on Generative AI applications and engineering problem - solving at Ford. Collaborating with cross - functional teams to innovate and improve technology solutions in the automotive sector.
AI Engineer/Data Scientist in Ford's Global Data Insights & Analytics team. Developing advanced AI/ML solutions and collaborating on cloud - native data products.
Data Scientist transforming customer data into insights that guide strategic decisions for Riachuelo. Collaborating with teams to analyze and visualize data trends for business growth.
VP, Credit Risk & Data Science overseeing credit risk framework and portfolio management at Purpose Financial. Leading strategy and governance to enable profitable growth and risk mitigation.
Data Scientist joining a leading economic consultancy to implement data science solutions for business challenges and advance thought leadership in advanced analytics.
Student assistant supporting the Joint Innovation Hub in developing innovative AI solutions at Fraunhofer ISI. Engaging in projects involving data science and generative AI in collaboration with industry partners.
Senior Data Scientist specializing in Large Language Models at Kyndryl's AI Innovation Hub. Leading the design and deployment of transformative AI solutions for forward - thinking enterprises.
Senior Data Scientist developing advanced machine learning models to solve complex business problems at Kyndryl's AI Innovation Hub in Spain. Leading model lifecycle with collaboration among AI architects and engineers.
Principal Data Science Consultant focused on translating KPI outcomes into strategic decisions. Leading customer workshops and supporting product development with Luminate expertise.