Senior Data Scientist (US)
Location
United States
Posted
74 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist (US)
Lynx Analytics
COMPANY OVERVIEW Lynx Analytics was founded in 2010 by a group of INSEAD students and professors with a strong research background in graph analytics. Several of our founders since then became professors and faculty directors of analytics centers at leading US universities. Our founding purpose? To apply graph theory to simplify and solve complex, real-world business problems. Our mission has evolved over the years, and we currently offer a range of cutting edge data analytics and AI solutions to help companies transform their operations and optimise their commercial performance. Back then, graph theory was mostly the purview of social networking sites. We wanted to expand this technology and help companies leverage their communities to unlock greater growth. Lynx has offices in Singapore, US, Hong Kong, Hungary, and operations in several other countries such as Canada, Germany, Indonesia. We work with some of the world’s largest companies and are constantly looking to expand our knowledge base and geographical footprint. Lynx Analytics’ technology is deployed with various Clients internationally and has significant growth potential. We have a diverse and inclusive global team comprising Professors, PhDs, MSc’s, and MBAs from Ivy Leagues, INSEAD and NUS with a broad spectrum of experience in start-ups and blue-chip companies (Google, Databricks, ZS, Abbvie, Amgen, Vodafone, Morgan Stanley, Palantir, Katana Graph to name but a few). It is the combination of our industry insight and experience, scalable proprietary technology, and highly qualified people that drives our compelling value proposition. We are looking for ambitious, innovative, empathetic and relentless team players to explore the career opportunities that we offer as we continue to scale our operations. About the role: We are looking for a Senior Data Scientist to work on and lead complex data analysis projects using standard modelling, data transformation approaches and Generative AI. They should be comfortable working with very large data sets residing in different data stores in disparate formats. The role requires the candidate to be strong with hands-on implementation and has the potential to move fast onto a high-growth career trajectory. Our future colleagues must have excellent communications skills as well as being able to visualize and present complex Data Science solutions for the main (C-level) stakeholders of the projects. Leadership experience and charisma are huge advantages. Key responsibilities will include: - Designing and Delivering Solutions for a defined Data Science Related Problem - Present the results / Prepare Presentations for the Project Stakeholders - Create reusable documentations, presentations and code libraries during the projects - Participating in internal education and research tasks - Leading smaller data science tasks with the help of internal leadership and PMO To succeed in this role, you should fulfill the following requirements: - More than 8 years of overall experience in data science field. - Experience in the life sciences industry is preferred - Mathematics, Statistics, Economics, Computer Science, Engineering or related degree (MSc or PhD is preferred) - Understanding complex Data Science Solutions - Solid knowledge of probability theory, statistics, data science algorithms and their application in Customer Retention, Campaign Management etc. areas - Good Communication (both verbal and written) and Data Visualization Skills - Coding abilities at least one of the following languages: Python (preferred), R, SAS, C, JAVA (or similar) - Solid experience in LLM / NLP Why You Will Love It Here: - Work on real-world AI and advanced analytics solutions with measurable business impact. - Collaborate with a global team of engineers and data scientists. - Exposure to diverse industries, modern cloud platforms, and cutting-edge AI technologies. - A collaborative culture that values real outcomes - High ownership, zero micromanagement - Rapid learning opportunities and diverse challenges - Flexible work hours, remote-friendly setup - Flat organisational hierarchy with high visibility and accessibility to our leaders
Job Requirements
- More than 8 years of overall experience in data science field.
- Experience in the life sciences industry is preferred.
- Mathematics, Statistics, Economics, Computer Science, Engineering or related degree (MSc or PhD is preferred).
- Understanding complex Data Science Solutions.
- Solid knowledge of probability theory, statistics, data science algorithms and their application in Customer Retention, Campaign Management etc. areas.
- Good Communication (both verbal and written) and Data Visualization Skills.
- Coding abilities at least one of the following languages: Python (preferred), R, SAS, C, JAVA (or similar).
- Solid experience in LLM / NLP.
Benefits
- Work on real-world AI and advanced analytics solutions with measurable business impact.
- Collaborate with a global team of engineers and data scientists.
- Exposure to diverse industries, modern cloud platforms, and cutting-edge AI technologies.
- A collaborative culture that values real outcomes.
- High ownership, zero micromanagement.
- Rapid learning opportunities and diverse challenges.
- Flexible work hours, remote-friendly setup.
- Flat organisational hierarchy with high visibility and accessibility to our leaders.
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
• Building and deploying predictive models • Working with large-scale datasets and turning them into actionable insights • Collaborating closely with data engineering and business teams • Covering the full analytics cycle: from hypothesis → modeling → deployment • Exploring modern areas like LLMs and AI-driven analytics.
Senior Applied AI Machine Learning Engineer – Claims Data Science
The HartfordFounded in 1810, The Hartford is one of the nation's largest investment and insurance companies. As an employer, The Hartford has been named among the region's Top Employers with a
• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies. • Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage. • Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations. • Accountable for design, development and maintenance of Models as Service • Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences. • Collaborate with partners Enterprise Data, Data Science, Business, Cloud Enablement Team, and Enterprise Architecture teams • Delivery of critical milestones for model deployment in the AWS and GCP clouds. • Adopt and promote MLOps best practices to the Data Science community. • Proactively monitor cloud usage to drive cost-saving opportunities across cloud accounts and deployed infrastructure.
• Serve as a founding member of the company’s data science function, building a culture of collaboration, growth, and excellence that will attract talent for years to come • Design metrics, build data pipelines, run experiments, launch models – apply a broad toolkit to expansive data from a rapidly growing business • Work closely with department leads and their teams to ensure our decision-making and operations are data-informed • Interpret data as the collective voice of our clients, generating insights that inform our product roadmap and user experience • Hold teams accountable to measurable impact, enabling them to identify and target their most effective levers to improve the business
Data Scientist – Active Secret Clearance
General DynamicsA business unit of General Dynamics, General Dynamics Information Technology (GDIT) supports some of the United States' most complex government, defense, and in
• Transform technology into opportunity as a Data Scientist with GDIT • Drive innovation and provide transformative solutions to our clients’ big-data obstacles • Design and develop statistical analyses (including predictive, inferential, supervised, non-supervised, ensemble and clustering) • Visualize the output of statistical models, and present and interpret the output for the corresponding client audience and group • Perform initial ETL and cleaning as necessary in preparation for modeling • Perform exploratory data analysis and model-fitting to reveal data features of interest to include machine learned and predictive modeling • Develop conceptual design and models to address mission requirements • Develop qualitative and quantitative methods for characterizing datasets in various states; and perform analytic modeling, scripting, and/or programming • Create and maintain report specifications and process documentation as part of the required data deliverables • Evaluate, document, and communicate research processes, analyses, and results to customers, peers, and leadership using the data science methodology framework



