Job Type

Our client is a biotech startup that is looking to create a better world by harnessing proteins to unlock lifesaving therapies.

We are looking for Data Scientists with all levels of experience, you must be ready to work with a small team & help the company develop strategies for growth and product.


  • Show leadership in computational analysis, statistical design, and predictive modeling
  • Interpret data science problems to product objectives
  • Create algorithms for in vivo and in vitro analysis & design
  • Support activities in the pre-clinical and clinical field



  • Masters or PhD in a scientific field (bioinformatics, biostatistics, etc)
  • 7-10 years of experience working as a data scientist
  • Technical proficiency with R & Python
  • Experience working in pre-clinical and clinical



  • Insurance (health, dental, vision)
  • Paid PTO & holidays
  • Competitive salary & stock options

Our client are a B2B data analytics Startup that give companies the power to solve business problems through discovering the consumers in their data and understanding how they think.

They are looking for an insightful, introspective, and inquisitive Data Scientist to join thier growing team where you will be presenting insights to customers and thrive in situations where you learn about and solve a customer specific problems.

This is a complete remote position with the option to work from their home office. 


  • Build, develop, and deploy models and algorithms using customer, open source, and proprietary data; assess model quality, and validate and iterate on those models

  • You will own the process of integrating customer data, analyzing it using our methodology and your data instincts, and make it deliver value to the customer

  • Evaluate the effectiveness and accuracy of public and private data sources, choose the right ones for their platform.

  • Help design and automate our customer dataset analysis and insights delivery process, to smoothly handle a wider variety and higher velocity of data

  • Act as the liaison between the customer and the product, making our tools useful, relaying product feedback, and customizing to a customer as needed.

  • Leaning on your empathy and leadership skills, you will work with our clients in a consultative capacity, learning about their specific necessities and being their advocate both internally and externally. That means participating in client meetings, leading technical discussions, presenting project results, interacting with clients in a consultative manner, and other technical customer-facing engagement, as needed.

Professional Requirements

  • 2+ years of experience in data science; strong preference for additional experience in software, R&D, consulting or adjacent fields.

  • Bachelor’s degree or equivalent experience in computer science, mathematics, statistics, economics, or similar.

  • Understanding of cluster-analysis techniques (K-means, DBSCAN, etc).

  • Excellent communication skills; comfortability with presenting presentations.

  • Comfortable with Python and common accompanying tools including Pandas and Scikit-Learn.

  • Deep understanding of statistics and other mindsets for building models from data; strong data acumen in translating business problems into supervised/unsupervised machine learning problems.

  • Comfortability with relational database systems and SQL.

  • Authorization to work in the US.

Preferred Skills and Experience

  • Passionate about discovering the secrets and solutions hidden in large datasets.

  • Highly attentive to detail, with a skeptical sixth sense about signal-vs-noise.

  • Ability to self-motivate, self-organize and work independently in a challenging, fast-paced environment with several ongoing concurrent projects.

  • A willingness and demonstrated ability to work collaboratively with a small team; excellent internal communication skills.

  • A can-do mentality, with the willingness to roll up your sleeves and take initiative to solve something when necessary.

  • Knowledge of a wide variety of machine learning and statistical analysis techniques, their advantages and drawbacks, and areas of best applicability.

  • Experience in designing and implementing effective monitoring systems for machine learning models in production.

  • Familiarity with machine learning approaches for time series forecasting and natural language processing (NLP).

  • Curious and eager problem solver, willing to bring new ideas to the team and advocate for best practices, and able to self-teach new skills when needed, with a hunger for building well-designed, high-quality solutions

  • Recognition that there are always multiple answers to a problem and the ability to engage in a constructive dialogue to find the best path forward.

  • A bit of experience with ETL processes or Data Prep tools is useful.

  • Experience in a Startup environment is helpful.

  • Ability to commute to the office quarterly, for all-staff meetings, and to travel to customer sites when necessary for a project.

Our client is a targeted precision medicine company for cardiovascular disease. Their mission is to improve access and outcomes for people with heart conditions.

What you will do
  • You will be a hands-on individual contributor using your skills in clinical data analysis to implement study protocols and publish your analyses in high-impact clinical journals as the first author.
  • You will use your constantly growing expertise in working with big messy data (e.g. electronic health records, claims, etc.) to create cohorts of eligible populations.
  • You will use your skills in R and/or Python and your dedication to open and reproducible science to develop libraries that we can use to easily describe, predict, and estimate clinical effects of interest.
  • You will contribute to rigorous and reproducible scientific publications

Required Qualifications:
  • MD, or PhD in Data Science, Epidemiology, Public Health, Computational Biology, or related field.
  • 5+ years of experience in: epidemiology, biostatistics, health economics, applied statistics, or related field.
  • At least one first author publication, or previously led a similarly complex project from start to finish.
  • Hands-on experience in at least one project using large healthcare data, such as claims or electronic health records.
  • Completed at least one complex project using R or Python and relevant data science libraries (e.g. tidyverse, sklearn, etc.).
  • Familiar with best coding practice, including functional programming, style guides, version control, and appropriate levels of documentation.
  • Experience implementing and interpreting statistical inference and modelling methods within Bayesian paradigms (e.g. t-test, Cox regression, etc.).
  • You can use and interpret epidemiologic concepts (e.g. study design, odds ratios, etc.) and can differentiate between statistical and clinical significance.
  • You have published 1+ clinical research articles as the first author.
  • You have experience with 1+ of SQL, Julia, Docker, Git.
  • You have experience in time series analyses and/or signal processing.
  • You are excited about transparency, rigor and reproducibility in biomedicine.
  • You can articulate technical concepts to a non-technical audience

Boston | New York | San Francisco | Hybrid

Our client is a technology company that is applying human and machine intelligence to accelerate the creation of life-changing medical treatments. They are building a best-in-class platform focused on developing and advancing new medicines. As part of a wider data team, you will be working with top level data scientists and engineers. You will develop solutions covering the gambit of diverse data including medical records, clinical trial data, imaging, genomics, etc. developed from our own labs. Our platform encompasses an end-to-end, integrated drug discovery and development engine that is being built from the ground up.


We are looking for a senior-level Data Scientist / Data Wrangler to join the Clinical Data Science, Real World Evidence team to advance our preclinical programs and drive development of our drug-discovery platform. You will execute complex initiatives and lead projects aimed at leveraging and maximizing the potential of real-world data (RWD) within our broader data ecosystem.


Day to Day

  • Execute complex initiatives and lead projects aimed at leveraging and maximizing the potential of real-world data (RWD) within our broader data ecosystem.
  • Define the data harmonization standards and curation strategy for RWE and clinical data within the company and in partnership with various stakeholders from engineering to therapeutics.
  • Partner with the Data Science Clinical Support Insights team to design pipelines to create Fit-for-Purpose data products from traditional RWD sources, unstructured/semi-structured EMR and research grade data that will support downstream clinical programs, insights generation, and algorithmic development.
  • Collaborate with software and data engineers to create reusable tools/packages, to generalize data processes, and to productionize and automate data transformation.



  • MS/ PhD in a computational science, data science, engineering or related fields, with 4+ years of industry experience (including post-doc) in a collaborative settings to unravel complex biological problems and communicate domain knowledge to non-computational stakeholders & colleagues
  • Knowledge of medical coding ontologies used in US and globally (ICD, ATC, LOINC, SNOMED, MedDRA etc.)
  • Expertise in strategic data search, data harmonization, quality and capability evaluation.
  • Fluency in python (required) and SQL.
  • Familiarity with at least one distributed computing library (such as Spark or Dask) and hands-on experience with pipeline development.
  • Basic understanding and experience on cloud computing (AWS), linux environment, and shell scripting.
  • Familiarity and/or experience with real-world evidence (RWE) studies or RWE-informed clinical trial design.
  • Familiarity and/or experience with cardiovascular, metabolic, and renal disease areas
  • Familiarity and/or experience with data formats and standards used in EMR systems and clinical trials such as HL7, CDISC, CDASH, ADaM, OMOP
  • Familiarity and/or experience with drug development process.
  • Familiarity and/or experience with designing python libraries or packages in other languages

Company Overview:

  • Fortune 500 company
  • Involved in Banking, Wealth Management, Financial Consultations, Life Insurance etc.
  • Large office located in the heart of New York City

Job Summary:

  • Work with Technology groups and business partners
  • Resolve any issues that may arise
  • Must have an understanding of predictive analytics 



  • Manages existing and future data science solutions,
  • Supervise appropriate reporting
  • Collect feedback and explore external landscape to plan features
  • Manage the full product planning from the data science side
  • Explore use cases for the Finance, Marketing, and Agency teams
  • Understand pain-points to identify possible data science solutions. 
  • Create value for the products the role manages
  • Participate in technology planning
  • Collaborate with project managers, data scientists and data engineers
  • Partner with our model governance and monitoring team
  • Develop and manage product roadmaps
  • Research external and internal data sources that may enhance our products
  • Follow industry trends in insurance
  • Assure compliance


Required qualifications

  • Degree (Master’s is preferred)
  • 5+ years of product management experience, 
  • 3+ years of experience working with data and analytics products.
  • 2+ years of underwriting-related experience
  • Solid understanding of predictive modeling
  • Strong written and oral communication skills
  • Familiarity with consumer financial regulatory environment
  • Familiarity with the consumer financial data vendor landscape

Company Overview:

  • Fortune 500 company
  • Involved in Banking, Wealth Management, Financial Consultations, Life Insurance etc.
  • Large office located in the heart of New York City

Job Summary:

  • Build a lot of predictive modeling solutions
  • Work on Agency and Investments data science products.
  • Good understanding of predictive analytics (including the process of building and deploying models) and technology is essential.




  • Lead data analysis and modeling projects 
  • Perform analysis and modeling to final reports/presentations
  • Communicate results to leadership
  • Demonstrate to stakeholders how analytics can be implemented to maximize business benefits.
  • Drive the use of data-based decision making and Analytics 
  • Utilize advanced statistical/AI techniques
  • Create high-performing predictive models 
  • Utilizes scientific approaches 
  • Verify the performance of algorithms and/or predictive models.
  • Works closely with business and technology partners 
  • Management track: potential to manage direct reports.
  • Follows industry trends in insurance
  • Assures compliance with regulatory and privacy requirements


Required qualifications

  • Graduate-level degree
  • 5+ years of experience with predictive analytics in financial services or insurance 
  • Experience using Machine Learning/AI in investment/quant settings
  • Basic knowledge in stochastic modeling and derivative pricing
  • Strong verbal and written communications skills
  • Effective presentation skills
  • Proficiency in creating effective and visually appealing PowerPoint presentations
  • Strong expertise in statistical modeling techniques
  • Substantial programming experience
  • Experience with data visualization