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An exciting Senior Data Scientist position is available within our innovative Data Science division, focusing on Generative AI. This role is a part of our journey towards becoming a cutting-edge insurance provider, placing a high emphasis on customer wellbeing. The selected candidate will have the unique opportunity to work alongside our Chief Data & Analytics Officer and Head of Data Science, playing a key role in our company's evolution.

Our Enterprise Data and Analytic Office leads the way in cultivating a data-driven culture, which is integral to achieving our strategic goals. The team’s responsibilities span across data lifecycle management, insight generation, and the delivery of data products. Comprising data analysts, product owners, engineers, scientists, and business-oriented data professionals, our efforts are crucial in driving revenue growth, risk management, and enhancing customer experience.

The primary focus of the Data Science Lab (DSL) is to revolutionize our approach to insurance through innovative technology and research, enabling us to adapt to changing societal needs and technological advancements. The DSL is pivotal in accelerating our transition to data-centric decision making and fostering long-term innovation.

For the Senior Data Scientist role, we are seeking an individual with a solid background in Large Language Models (LLM) and Generative AI. The responsibilities include developing advanced data science solutions using machine learning and artificial intelligence, influencing innovation across various business areas and products. This role involves working closely with senior management on impactful projects, delivering AI/ML solutions that have a substantial effect on risk management and overall financial performance. Ideal candidates should have expertise in insurance and financial services, a fervor for modern ML and AI technologies, and the capability to develop data science strategies that support business growth and customer satisfaction.

Responsibilities:

1. Develop Generative AI and LLM capabilities:

   • Undertake projects involving the analysis of unstructured data like insurance contracts and medical records.
   • Implement AI/ML solutions for enhancing underwriting, claims processing, and customer service.
   • Conduct large-scale experiments, including model training, fine-tuning, and prompt engineering.
   • Develop and scale LLM models for both development and production stages.

2. Develop Enterprise Test and Learn Capabilities:

   • Explore state-of-the-art experimentation and causal inference/ML techniques.
   • Execute advanced data-driven experiments to optimize business aspects.

3. Support the Data Science Lab (DSL):

   • Engage in various stages of project development from initial data exploration to final reporting.
   • Utilize advanced statistical and AI/ML techniques for predictive modeling and analyses.
   • Ensure data quality and integrity in both development and production stages.

4. Contribute to the Data Science organization:

   • Work collaboratively with teams across Data Science, Data Engineering, and Business groups.
   • Standardize tools, processes, and best practices in Data Science.

Candidate Profile:

• Passionate about groundbreaking technology, particularly AI/ML.
• Experience in developing and implementing data and analytic solutions.
• Collaborative mindset, working effectively with multidisciplinary teams.

Qualifications:

• PhD or Master’s degree in Statistics, Computer Science, Engineering, or related fields, plus relevant professional experience.
• Strong foundation in ML modeling, probability, statistics, and causal inference.
• Proficiency in Python programming, PyTorch, Tensorflow, and parallel computing for ML.

Location and Salary:

• Hybrid remote position, with two days a week in our New York, NY, Bethlehem, PA, Holmdel, NJ, or Stamford, CT offices.
• Salary range: $111,840.00 - $183,735.00, plus potential for additional compensation.

An exciting opportunity has arisen for a Lead Data Scientist within our Data Science division. This pivotal role is focused on leveraging cutting-edge technologies and innovative approaches to propel our company towards a more data-centric future, enhancing our capabilities in decision-making and insight generation. The successful candidate will be at the forefront of integrating advanced data science methodologies, including machine learning and artificial intelligence, to catalyze innovation across our product lines and services.

As the Lead Data Scientist, you will play a key role in establishing and guiding our Data Science Lab. Your expertise will be instrumental in developing sophisticated data science solutions, employing state-of-the-art machine learning and artificial intelligence techniques. This role involves close collaboration with top-tier executives on significant projects, delivering AI/ML solutions that are market-ready and have a tangible impact on our risk management strategies and financial outcomes. Ideal candidates should possess profound knowledge in the fields of insurance and financial services, a zeal for applying the latest ML and AI techniques, and the capacity to create and implement effective data science strategies that promote growth, competitive edge, and customer satisfaction.

We are undergoing a transformation to become a contemporary, progressive insurance entity, focusing on enhancing customer well-being. A Chief Data & Analytics Officer (CDAO) has been appointed to steer this shift, leading our Enterprise Data and Analytic Office (EDAO). This position offers a unique chance to work alongside the CDAO and the Head of Data Science, contributing significantly to our ongoing development.

The EDAO is committed to fostering a culture that prioritizes data-driven insights, playing a crucial role in achieving our strategic goals. Our main activities include deriving business value from data and analytic products, managing data lifecycles, generating insights, and delivering data products. The team comprises data analysts, product owners, engineers, scientists, and business-focused data leaders. Our work is vital to the company's revenue growth, risk management, and customer experience enhancement.

Key Responsibilities:

1. Lead the Data Science Lab (DSL):

   • Establish and head a team of skilled data scientists.
   • Remain abreast of ML and AI advancements and industry trends.
   • Partner with external entities for the development and testing of novel AI/ML methods.
   • Apply ML and AI innovations to practical scenarios within our company.
   • Implement test-and-learn methodologies for new data science applications.
   • Mentor and guide DSL team members.
   • Innovate and patent new technologies and methodologies.
   • Serve as a data science authority in internal and external interactions.
   • Engage in proof-of-concept tests for new data, software, and technologies.
   • Participate in AI/ML and industry conferences.

2. Develop Advanced AI/ML Solutions:

   • Utilize AI/ML for complex tasks like mining unstructured data (insurance contracts, medical records, etc.).
   • Innovate in areas like underwriting risk assessment and customer service using AI/ML.

3. Contribute to the Overall Data Science Organization:

   • Collaborate across various teams (Data Science, Data Engineering, Business groups).
   • Standardize tools, processes, and best practices within Data Science.

Candidate Profile:

• A deep passion for cutting-edge technology, particularly in AI/ML.
• Proven experience in developing and implementing data and analytic solutions to solve complex business challenges.
• Leadership qualities, with experience in managing data science teams.
• Strong analytical skills and a detail-oriented approach.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Applied Mathematics, or related fields, with over 10 years of experience.
• Advanced degrees (PhD or Master's) with significant experience preferred.
• Extensive hands-on experience in ML modeling and development.
• Proficiency in deep learning models, including Large Language Models (LLM) and Natural Language Processing (NLP).
• Expertise in Python programming, PyTorch, Tensorflow, and parallel computing for ML.

Location and Salary:

• This remote position offers flexibility, with occasional travel required.
• Salary: $140-240k DOE, with potential for incentive compensation.

Our Commitment:

We strive to provide a supportive and flexible environment, offering numerous opportunities for professional and personal growth. We are dedicated to fostering well-being, providing comprehensive health care options, retirement plans, and a range of other benefits. Our commitment to diversity and inclusion is unwavering, ensuring an equitable and enriching workplace for all employees.

 

We are a cutting-edge biotech company dedicated to revolutionizing drug discovery and development through the integration of machine learning and computational chemistry. We are seeking a highly skilled and motivated Machine Learning Engineer to join our team and play a pivotal role in building our computational chemistry engine for drug discovery.

Responsibilities:

• Development of Computational Chemistry Engine:

  • Design, develop, and optimize a state-of-the-art computational chemistry engine tailored for drug discovery, leveraging machine learning techniques to enhance accuracy and efficiency.

• Machine Learning Model Development:

  • Build and deploy machine learning models for various stages of drug discovery, incorporating predictive modeling, clustering, and classification algorithms to analyze biological and chemical data.

• Integration of Machine Learning into Computational Chemistry:

  • Apply machine learning methodologies to traditional computational chemistry processes, integrating data-driven insights to enhance predictive modeling and accelerate drug discovery timelines.

• Cheminformatics:

  • Utilize cheminformatics principles and techniques to organize, analyze, and extract meaningful insights from chemical and biological data, contributing to the development of novel drug candidates.

• Collaboration and Cross-Functional Communication:

  • Collaborate closely with computational chemists, biologists, and other cross-functional teams to understand their requirements and integrate machine learning solutions effectively into the drug discovery pipeline.

• Model Deployment and Productionization:

  • Develop strategies for deploying machine learning models into production environments, ensuring scalability, reliability, and seamless integration with existing systems.

• Performance Optimization:

  • Continuously optimize machine learning models and algorithms to improve prediction accuracy, computational efficiency, and overall system performance.

       
      Qualifications:

• Bachelor's, Master's, or Ph.D. in Computer Science, Computational Chemistry, Bioinformatics, or a related field.
• Proven experience in building and deploying machine learning models in a production environment, preferably in the biotech or pharmaceutical industry.
• Strong expertise in computational chemistry, cheminformatics, and traditional computational chemistry techniques.
• Proficiency in programming languages such as Python, and experience with machine learning frameworks and libraries like TensorFlow, PyTorch, scikit-learn, etc.
• Knowledge of drug discovery processes, including target identification, lead optimization, and ADMET properties.
• Excellent problem-solving skills and the ability to work in a collaborative, fast-paced team environment.

???????    Preferred Skills:

• Familiarity with cloud computing platforms and technologies.
• Experience in working with large-scale biological and chemical datasets.
• Knowledge of regulatory requirements and best practices in drug discovery.

Company Overview: Join a Fortune 50 financial services firm at the forefront of innovation, leveraging cutting-edge technologies and data-driven strategies to optimize decision-making and drive business growth. As a Director of Data Science with a strong focus on Geo-Spatial data, you will lead a high-performing team of data scientists, drive strategic initiatives, and contribute to the success of the organization.

Key Responsibilities:

1. Leadership and Strategy:

   • Develop and communicate a comprehensive data science strategy aligned with the company's overall business objectives, with a specialized focus on Geo-Spatial data analytics.
   • Lead and mentor a team of data scientists, providing guidance on technical expertise, project management, and professional development.

2. Geo-Spatial Data Analysis and Modeling:

   • Utilize advanced analytics techniques to extract insights and patterns from Geo-Spatial data, providing valuable business intelligence and supporting decision-making.
   • Build and deploy complex models and algorithms to solve geo-spatial challenges, integrating data sources such as GPS, satellite imagery, and location-based services.

3. Technology and Tools:

   • Leverage a diverse set of technologies and tools, including Python, R, SQL, arcGIS, PySpark, and PyTorch, to develop robust and scalable data science solutions.
   • Stay updated with emerging technologies in Geo-Spatial data analysis and continuously enhance the team's technical capabilities.

4. Collaboration and Stakeholder Engagement:

   • Collaborate with cross-functional teams and stakeholders to identify business requirements and ensure data science initiatives align with organizational needs and objectives.
   • Translate complex technical findings into actionable insights and recommendations for both technical and non-technical stakeholders.

5. Project Management and Execution:

   • Oversee end-to-end project lifecycle, from project initiation to deployment, ensuring timelines and deliverables are met within defined budgets and scope.
   • Manage resources effectively to optimize project execution, prioritize tasks, and allocate work to achieve maximum efficiency and productivity.

Qualifications:

• Education: Master's or Ph.D. in a relevant field such as Data Science, Computer Science, Statistics, Geography, or a related discipline.
• Experience: 5 years of experience focused on Geo-Spatial data analysis and modeling.
• Technical Skills:
  • Proficiency in Python, R, SQL, arcGIS, PySpark, and PyTorch.
  • Strong knowledge of Geo-Spatial data analysis, GIS principles, and mapping technologies.
• Leadership and Management:
  • Proven experience in leading and managing a team of data scientists.
  • Excellent communication and interpersonal skills, with the ability to effectively collaborate and influence stakeholders at all levels.
• Strategic Thinking:
  • Ability to develop and execute data science strategies aligned with organizational goals and industry trends.
  • Strong business acumen and strategic thinking to drive the use of data science for competitive advantage.

We Offer:

• Competitive compensation package and performance-based incentives.
• Comprehensive benefits, including healthcare, retirement plans, and employee wellness programs.
• Opportunities for career growth and advancement within a globally recognized Fortune 50 financial services firm.
• A collaborative and innovative work environment that fosters creativity and encourages continuous learning and development.

Salary range: $150,000-$230,000 

Join our team and contribute to revolutionizing data science in the financial services industry with a focus on Geo-Spatial analytics!

Company Overview:

Join a dynamic and innovative healthcare-focused organization at the forefront of leveraging advanced technologies in data science. As a Senior Data Scientist specializing in Natural Language Processing (NLP) and Large Language Models (LLMs), you will play a pivotal role in building end-to-end data science projects that transform healthcare data into actionable insights, ultimately improving patient outcomes and healthcare delivery.

 

Key Responsibilities:

NLP and LLM Model Development:

• Develop state-of-the-art NLP and LLM models to extract valuable information and patterns from electronic health records, medical records, and medical claims data.
• Optimize and fine-tune models for accuracy, efficiency, and scalability, ensuring they can handle high volumes of healthcare data in production environments.

End-to-End Data Science Projects:

• Lead the design, development, and deployment of end-to-end data science projects from data collection and preprocessing to model development, evaluation, and production deployment.
• Collaborate with cross-functional teams to ensure seamless integration of NLP and LLM models into healthcare systems and processes.

Data Processing and Integration:

• Engineer and preprocess healthcare data to ensure it is suitable for modeling, addressing challenges such as data cleaning, data augmentation, and feature engineering.
• Integrate various data sources and types, including electronic health records, medical records, and medical claims data, to derive comprehensive insights.

Performance Monitoring and Optimization:

• Establish monitoring systems to track model performance, detect anomalies, and measure the impact of models on healthcare outcomes.
• Continuously optimize models and algorithms to improve performance, scalability, and efficiency in real-world production settings.

Collaboration and Knowledge Sharing:

• Collaborate with multidisciplinary teams, including clinicians, data engineers, and product managers, to ensure the alignment of data science projects with organizational goals and objectives.
• Share knowledge and insights with the team, keeping them informed about advancements in NLP, LLMs, and healthcare data analytics.

Qualifications:

• Education: Master's or Ph.D. in a relevant field such as Data Science, Computer Science, Artificial Intelligence, or Healthcare Informatics.
• Experience:
• Minimum of 3 years of hands-on experience in data science, with a focus on NLP and LLMs in healthcare.
• Proven track record of successfully building and deploying data science projects in healthcare settings, particularly using electronic health records and medical claims data.
• Technical Skills:
• Proficiency in Python and relevant data science libraries (e.g., NLTK, spaCy, transformers).
• Strong understanding of NLP techniques, LLMs (e.g., BERT, GPT), and deep learning architectures.
• Experience working with healthcare data, including electronic health records and medical claims data.
• Healthcare Domain Knowledge:
• Understanding of healthcare terminologies, healthcare systems, and healthcare data privacy and compliance standards (e.g., HIPAA).
• Communication and Collaboration:
• Excellent communication skills, with the ability to effectively convey complex ideas and findings to both technical and non-technical stakeholders.
• Proven ability to collaborate in a team-oriented environment and work effectively across multiple departments.

 

Join us in revolutionizing healthcare data science with NLP and LLMs, and make a significant impact on patient care and outcomes!

 

Apply directly or send your resume to angelo@alldus.com!

About Us:

We are a cutting-edge AI-powered Healthcare SaaS Data Company at the forefront of using real-world evidence and AI technology to empower healthcare professionals and institutions in making data-driven decisions. We leverage our expertise in healthcare study design, research methodologies, and Real World Data (RWD) analysis to transform the healthcare landscape. If you're passionate about revolutionizing healthcare through data science and AI, this is the place for you.

 

Job Description:

As a Data Scientist, you will play a pivotal role in advancing our mission to revolutionize healthcare decision-making by harnessing the power of AI and real-world evidence. You will work closely with cross-functional teams to develop innovative solutions that enable healthcare professionals to make informed decisions, improve patient outcomes, and enhance overall healthcare delivery.

 

Key Responsibilities:

• Data Analysis and Modeling:

1. Collaborate with multidisciplinary teams to analyze complex healthcare data, including Claims Data and Electronic Medical Records (EMR) data, and apply advanced machine learning and statistical techniques to extract valuable insights.

• Healthcare Study Design:

1. Design and execute healthcare studies, ensuring the selection of appropriate methodologies, data sources, and research strategies.

• Algorithm Development:

1. Develop and implement machine learning algorithms to predict healthcare outcomes, identify trends, and support clinical decision-making.

• Data Visualization:

1. Create clear and impactful data visualizations using Python Data Science stack (Pandas, Numpy, Matplotlib, Seaborn) to communicate findings effectively to both technical and non-technical stakeholders.

• Model Evaluation:

1. Conduct rigorous evaluation of models and methodologies, ensuring their reliability and validity in real-world healthcare settings.

• Collaboration:

1. Collaborate with cross-functional teams, including data engineers, software developers, and domain experts, to integrate data science solutions into our healthcare SaaS platform.

 

Qualifications:

• Ph.D. in Data Science, Computer Science, Statistics, or a related field.
• 5+ years of experience in the Healthcare or Biotech industry.
• Strong background in healthcare study design and research methodologies.
• Proficiency in working with Real World Data, particularly Claims Data and/or EMR data.
• Expertise in Python Data Science stack, including Pandas, Numpy, Matplotlib, Seaborn, SciPy, and Scikit-Learn.
• Experience with machine learning and statistical modeling techniques.
• Strong problem-solving skills and the ability to work independently and collaboratively.
• Excellent communication skills to convey complex findings to both technical and non-technical audiences.

 

Benefits:

• Competitive salary and performance-based bonuses.
• Comprehensive healthcare coverage.
• Generous vacation and paid time off.
• Professional development opportunities.
• A collaborative and innovative work environment.

 

Join us and be part of a dynamic team that is shaping the future of healthcare with AI and real-world evidence. Apply now to contribute to groundbreaking solutions that make a meaningful impact on patient care and healthcare decision-making.