Do you have a noticeable passion for results?
You’re bold, empathetic, and very resourceful, especially when results are at stake. You have what it takes: a competitive drive coupled with the exceptional ability to communicate the science behind our client’s products and build lasting business relationships. Such talent and passion make you the right fit for this Data Scientist
with Syneos Health.
As a Data Scientist
at Syneos Health
you Design, develop and program methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interact with product and service teams to identify questions and issues for data analysis and experiments. Develop and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identify meaningful insights from large data and metadata sources; interpret and communicates insights and findings from analysis and experiments to product, service, and business managers.Responsibilities
- Analyse structured and unstructured data sets using quantitative techniques to solve a wide range of business problems and address client needs
- Integrate and manage multiple healthcare-centric data sources for the purposes of deriving quantitative insights, developing machine learning based models, discovering and ranking features and statistical analysis (e.g. hypothesis testing).
- Use best industry practices to develop model validation and QA pipelines
- Efficiently and clearly, communicate complex statistical concepts and project goals to internal and external stakeholders
- Gather performance metrics and project requirements from business partners and clients to develop forecasting models, classifiers, and statistically based solutions
- Develop and deliver reports and presentations that clearly explain quantitative products and strategies to a wide range of internal and external audiences
- Explore data using programming skills to interpret large data sets from a variety of sources including finance, sales, and healthcare claims
- Background in data science and one or more of the following: statistics, computer science, business intelligence, library science, or equivalent experience.
- Capable of independently designing, conducting, and analyzing research projects.
- Capable of independently transforming, cleaning, and loading large data sets.
- Experience with digital/programmatic advertising, performance analytics, web scraping and NLP (a plus).
- Proficient with three or more of following methods: factor analysis, structural equation modeling, regression analysis, bayesian statistics, PCA, machine learning approaches (e.g., CART, MARS, kNN, Naïve Bayes, Regularization algorithms (e.g., Elastic net)).
- Proficient with the following technologies:
- SQL/NoSQL, Python and/or R, dashboarding and reporting platforms (e.g., Google Data Studio, Google Analytics, Power BI, as well as Python and/or R dashboarding libraries/packages (e.g., dash, r shiny)). Advanced Excel(Vlookup, Hlookup, sumifs etc),VBA, Macros, MIS Reporting, string matching and automating reports.
At Syneos Health, we believe in providing an environment and culture in which our people can thrive, develop and advance. We reward and recognize our people by providing valuable benefits and a quality of life balance.
- Familiarity with US healthcare marketing and/or medical billing practices in the US is a plus.
Why Syneos Health? Join a game-changing global company that is reinventing the way therapies are developed and commercialized. Here, you’re empowered to exceed your sales goals with the autonomy you need to over deliver. We’re dedicated to creating better, smarter, faster ways to get biopharmaceutical therapies to patients. Syneos Health has launched more sales teams in the last 5 years across all major Therapeutic Areas than the top 25 pharma companies combined. By joining Syneos Health, you’ll be connected to our multitude of career paths and pipeline of employment opportunities.