Data Jobs in Boston

The Pharmacy Informatics Lead will oversee Medical Formulary modeling and forecasting, as well as analytic support for Specialty programs.   The Lead leverages their advanced knowledge of data, modeling, optimization, and tools. Applies disciplined analytics to predict behavior and optimize programs and products to maximize revenue growth. Utilizes advanced or predictive modeling to develop, test and validate cases that improve the outcomes and quality of the programs we offer. Contributes to more innovative approaches to financial models as they build knowledge of the business context in which it operates. Understands and analyzes complex data, articulates mathematical concepts to various units within the company at the appropriate level, and on initiatives with potentially sizable dollar impact. Advises executives to develop functional strategies (often segment specific) on matters of significance. Exercises independent judgment and decision making on complex issues regarding job duties and related tasks, and works under minimal supervision. Uses independent judgment requiring analysis of variable factors and determining the best course of action.  This lead role will have a team of 4 associates to support this work. 

Our data science team is analyzing large data sets (we’re collecting billions of individual actions every month) and building products that enable our customers to grow faster and communicate more effectively with their customers. We’re looking for data science software engineers to build production features, models and pipelines.

BI Development: Build highly interactive dashboards and reports that are easy to understand, enable self-service and provide secure and efficient access to data. BI Solution Enhancement: Continuously improving and enhancing the performance, capabilities, and functional coverage of BI solutions. Ad-hoc Data Analysis: Extract and analyze data from disparate sources based on ad-hoc user requests. Work with business users and other internal customers to help prioritize self-service capabilities in the road map.

In this Data Engineer role, you will be involved in the transformation of sensor data and instrumentation that allow effective monitoring and reporting of the environments being sensed and of the sensors and networks we have deployed. The challenges are diverse as are the potential solutions, and you will have freedom to explore approaches to meeting the challenges coupled with responsibility for delivering effective analytic enabling products. You will have the opportunity to perform across a range of Data Engineering responsibilities and be constantly challenged to extend your skills and the solutions the Data Engineering team is able to provide.

We’re looking to bring aboard our first Data Scientist to develop next generation features into the LogRocket platform. LogRocket currently tracks millions of events across our customers’ web applications to ensure product teams can quickly identify and squash any bugs or errors that arise. We now want to leverage that data to uncover new aspects of user experiences and provide proactive, actionable insights to our partners to ensure they are building the best experience possible for their users. You will have millions of data points to explore and play around with on a daily basis, all while building the foundation for LogRocket’s Data Science team and function for years to come.

You will have the opportunity to work in a company culture that puts employees first, is relaxed but focused and hard-working. Every PathAI employee is a contributor to our mission to pioneer better patient care by providing the best, most innovative deep learning tools to biotech, pathologists, clinicians and healthcare organizations. You will work alongside leading innovators in the field of deep learning and medicine, and play a critical role in algorithm development.

Agero’s Data Science and Analytics team is developing a modern, cloud-based data platform to support our analytical products and machine learning pipelines. Our team is expanding and we are looking to add an experienced, self-motivated Senior level Data Engineer to help design and build out a curated, “single source of truth” data set that will feed a variety of downstream use cases including APIs, reports, dashboards, self-service tools, and modeling efforts. The platform will provide the Data Science and Analytics team along with the broader organization with a more secure, centralized, and reliable access to the company’s data. At the same time, it will reduce effort required to ingest new sources of data or to build new ETL processes to support new modeling or reporting use cases. 

As a scientist on our GeoInnovation Soil Carbon Science team, you will apply your extensive experience in soil ecology, biogeochemistry and carbon cycle science to assist Indigo’s efforts focused on increasing soil health and soil organic matter via regenerative management practices. Indigo in heavily invested in regenerative agriculture, and recently announced its Terraton initiative designed to aggressively sequester atmospheric carbon dioxide in agricultural soils. To meet the ambitious goals set out for Terraton, Indigo is building a team to support the scientific design and implementation of soil carbon models that will help Indigo quantify changes in soil carbon from different land management practices. As member of the soil carbon science team, you will be instrumental in driving the underlying science and supporting this modeling effort.

Generate dashboards and cards within Domo that track metrics across all levels of the organization. Partner with functional leaders to understand their business needs and the data sets required to support them. Integrate with their teams to establish strong professional relationships. Utilize Domo to create data sets that aggregate data from different sources with the goal of creating a full picture of the health and engagement of our client base. Examine existing processes and make recommendations to better enhance PI’s data structure, hygiene, and health across multiple systems. Create a unified and integrated view of our organization’s data that is aligned with our objectives and goals. Define and evolve cohort classification and assess how well lead generation, sales, product releases, onboarding programs, and other initiatives are impacting cohorts over time.

As a Data Engineer within the Revenue & Growth Metering team, you will work in Spark with big data tooling to build highly reliable, verifiably-accurate data processing pipelines for a high scale mission-critical process. This team ingests the full firehose of data we receive each day - literally trillions of data points and hundreds of TB’s.

Work with different(marketing, analytics, development) teams across the organization and tackle pixel/tag implementation requests in an efficient way within a tag manager (TealiumIQ). Use browser web debugging tools to perform tag validation and QA. Perform Tagging audits/data integrity checks on a regular basis to have better control over the tags deployed across the sites. Document and maintain a copy of tagging requests from the different teams. Use mobile proxy tools like Charles/Fiddler to validate analytics tagging across mobile applications and mobile web tagging. Collaborate with different vendors(marketing, social media, affiliates, etc.) to understand different analytics implementation techniques and suggest implementation best practices based on well defined organization standards.

Frame and conduct complex exploratory analyses needed to deepen our understanding of our users. Partner with product, business and strategy teams to contribute to product improvements and initiatives. Use machine learning and big data tools on tremendously large and complex data to deepen our data-driven advice and personalized modeling. Conduct research into various aspects of our business and employ statistical and modeling techniques when appropriate to make recommendations to non-technical stakeholders.

We’re looking for a data-savvy individual to join our Engineering team to design and build a data environment that is robust, high-quality, and blazingly performant. You’ll work with a highly skilled and motivated team. Your efforts and expertise will have a direct impact on framing and solving some of the most challenging problems in mobile commerce at a scale and complexity that few organizations can match. You care deeply about formalism & correctness; you have strong software and data modeling skills. Data is at the core of what we do at Hopper, both in providing data-driven travel advice to our users, and in analyzing our user behavior to improve the product experience and enable us to best manage our business.

As a Machine Learning Engineer, you will be responsible for tackling a wide range of problems from natural language processing to timeseries prediction. You will move beyond the theoretical confines of academia and apply your tradecraft to build machine learning systems on real world data. In this role you will constantly collaborate and work with groups of engineers. Our machine learning team is responsible for delivering ML-based solutions from problem framing, to prototyping, to production application. 

Support the day-to-day analytical needs of a cross-functional product development team. This includes assessing business opportunities, developing success metrics, designing and analyzing experiments, and building statistical models using large data sets. Identify, implement, and drive adoption of analytics-based solutions to business problems. Provide statistical support across all departments and for end customers. Mentor other team members. Innovate new ways data science can be used to support the organization and its mission.

· Regular evaluation of implemented tools for investment productivity and effectiveness. Continually assess functional capabilities vs. other tools in market and opportunities for enhancing existing or introducing new tools. · Evolve the existing landscape of reporting through developing new leadership level dashboards and presentations with consistent look and feel within the bounds of our brand. · Provide thought leadership and data journalism mentorship to other analysts. · Build and maintain the distribution of push reporting and self-service data products for all levels of the organization, enabling seamless access to information. Ensure federation of data assets while maintaining appropriate privacy and information security requirements. · Work with team partners on the architecture and supporting data structure to guarantee high-performance, scalable reporting solutions. Routinely assess reporting performance, intercepting impacts from technical changes and guaranteeing customer satisfaction. Define and manage SLA metrics to track the availability and quality of reports and dashboards.

Position summary: Research scientist in the Healthcare Research organization working on state-of-the-art deep learning systems for our Dragon Ambient eXperience (DAX) product.  Major duty is to help develop deep learning technology to improve physicians’ efficiency in clinical documentation, as well as develop tools to help other team members do similar research.

We are seeking a machine learning engineer excited to work with state-of-the-art models and cutting-edge research, as well as with parallel and concurrent algorithms. This person will work closely with our technical team, bringing deep learning product requirements to our engineers and putting machine learning research into practice within our software. If you are a machine learning engineer who wants to contribute to solving challenging technical problems at the forefront of machine learning, this is the role for you.

We are seeking an experienced machine learning engineer excited to work with state-of-the-art models and cutting-edge research, as well as with parallel and concurrent algorithms. This person will work closely with our technical team, bringing deep learning product requirements to our engineers and putting machine learning research into practice within our software. If you are a machine learning engineer who wants to contribute to solving challenging technical problems at the forefront of machine learning, this is the role for you.

Create, maintain, and enhance data ingestion and processing pipeline architecture all the way from the Edge to the Cloud and back to the factory floor. Build and manage streaming and storage systems for both real-time and batch analytics. Leverage scalable data streaming, processing, and storage systems such as Kinesis, Kafka, Spark, PostgreSQL. Champion code quality and data architecture improvements. Review code and provide/receive constructive feedback to help develop the team. Be a champion of our Core Values.