Machine Learning Engineer, HCP Engagement & Attribution

Remote: 
Full Remote
Contract: 
Work from: 

Offer summary

Qualifications:

3+ years of experience in building and deploying machine learning models in production environments, preferably in SaaS or marketing analytics., Deep expertise in multi-touch attribution, uplift modeling, and causal inference using experimental and observational data., Strong proficiency in Python and experience with ML libraries like scikit-learn and PyTorch, as well as MLOps tools., Familiarity with large-scale data systems and cloud platforms such as AWS or Azure..

Key responsibilities:

  • Design and operationalize attribution models to assess the impact of various omnichannel touchpoints on HCP prescribing behavior.
  • Collaborate with cross-functional teams to translate business questions into scalable data science solutions.
  • Build scalable ML pipelines and services using modern MLOps tools and cloud-native infrastructure.
  • Evaluate and enhance machine learning model performance using statistical methods and validation frameworks.

ODAIA logo
ODAIA Scaleup https://www.odaia.ai/
51 - 200 Employees
See all jobs

Job description

Machine Learning Engineer, HCP Engagement & Attribution 

ABOUT ODAIA

ODAIA noun
o·da·ia | 'oh-day-yeah
An Ancient Greek word referring to “tools of the trade.”

You can also find more information about the company and our products at odaia.ai.
ODAIA is a remote first organization, all our positions are WFH with frequent company and team based socials, events and meetings in-person and virtually. 

ODAIA's AI helps the world’s largest pharma commercial teams grow their brands by engaging HCPs at the right time—when they need information to make treatment decisions.
We use proprietary machine learning (ML) and large language models (LLMs) to help teams understand their customers—healthcare professionals (HCPs)—and predict prescribing behaviors.

Our SaaS platform turns complex data into personalized insights, helping pharma teams make informed decisions that bring therapies to patients faster.

ODAIAns (what we call ourselves) are inspired to reinvent the future of how non-technical people leverage data in their day-to-day lives. We are passionate about solving complex problems in data, AI, engineering, design, and product, so our customers don’t have to. We live by the notion that “simplicity is the ultimate sophistication;” and making simplicity scalable is an even bigger challenge. That’s why we have a crazy talented team led by serial entrepreneurs, tech veterans, and life sciences experts.


OUR MISSION

Reducing patients’ time to therapy by facilitating meaningful interactions with healthcare providers, through human-centric software powered by AI. 

We’re also on a mission to build an innovative, diverse, and ego-free business, where trust, innovation and ownership are valued. You’re on a mission too? We’re here for it. We put an emphasis on career development for our employees, and the opportunities to grow are extensive.

WHAT’S ON OFFER

Reporting to the Engineering Development Manager, the Machine Learning Engineer, HCP  Engagement Attribution will possess deep expertise in building attribution models to support omnichannel personalization in the pharma industry. This role is critical in helping ODAIA advance its ML-driven product capabilities by identifying the impact of specific touchpoints (e.g., rep visits, email campaigns, webinars) on HCP engagement and prescription behavior.


WHAT YOU WILL DO

  • Work with large-scale healthcare and engagement datasets (Rx, CRM, digital campaigns) to extract insights that drive product value
  • Design and operationalize attribution models that quantify the causal impact of omnichannel touchpoints (e.g., rep visits, emails, webinars) on HCP prescribing behavior
  • Collaborate with cross-functional teams to frame business questions as scalable data science solutions
  • Define success metrics and implement robust evaluation frameworks to ensure models are both accurate and actionable
  • Optimize for model explainability and usability within a commercial SaaS platform.
  • Build scalable ML pipelines and services using modern MLOps tools and cloud-native infrastructure
  • Rigorously evaluate and iteratively enhance machine learning model performance using appropriate statistical methods and validation frameworks
  • Proactively experiment with and integrate cutting-edge ML and causal inference methods into production environments
  • Champion collaboration and knowledge-sharing across teams to accelerate ML adoption and impact



WHAT YOU BRING

  • 3+ years of end-to-end experience building, validating, and deploying ML models in real-world production environments, ideally within SaaS or marketing analytics.
  • Deep expertise in multi-touch attribution, uplift modeling, and causal inference using both experimental and observational data.
  • Strong foundation in software engineering best practices, including version control, code readability, documentation, and reproducible research
  • Expert-level Python with production experience in ML libraries (e.g., scikit-learn, XGBoost, PyTorch) and orchestration tools (e.g., Dagster, Airflow)
  • Experience working with large-scale data systems (e.g., S3, Snowflake, DuckDB) and cloud platforms like AWS or Azure
  • Familiarity with MLOps tools (e.g., MLflow) for managing model lifecycles.
  • Clear, structured communicator with the ability to align technical outputs with business and product priorities.
  • Track record of delivering robust, research-backed ML solutions from concept to production and continuous iteration
  • Bonus: Familiarity with pharmaceutical/life sciences data (e.g., Rx claims, CRM, salesforce activity) and commercial strategy in regulated markets.



WHAT WE OFFER

  • A strong values based culture, we Ignite Innovation, Own It and Stand Together
  • Tremendous growth and unique learning opportunities
  • A large amount of ownership and autonomy for managing things directly
  • No waiting period for medical and dental benefits enrollment 
  • Flexible working hours, focusing on what we achieve and not the number of hours we clock
  • An open and flexible vacation policy
  • Stock option grants
  • Career development opportunities, and a solid business model - we’re in it for the long haul!


LOCATION

We are a remote first company with an office hub located in Toronto, supporting team building and social connectivity with virtual and in-person collaborative work sessions, team meetings and socials.

EMPLOYMENT VERIFICATION

Any conditional offer of employment made to a successful candidate will be subject to the full satisfaction with the results of any background and reference checks.

ACCOMMODATIONS AND ACCESSIBILITY

Accommodations are available on request for candidates with disabilities taking part in all aspects of our hiring process. For more on this, you can inquire about accommodations if you're invited to an interview.

DIVERSITY, EQUITY & INCLUSION

As an equal opportunity employer, ODAIA is committed to creating an environment that respects diversity and inclusion. ODAIA does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status.

At ODAIA, we are committed to building an environment where everyone feels included, valued, and heard. We are committed to creating a diverse workplace, and are an equal opportunity employer who does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status.

We strongly encourage applications from Indigenous Peoples, racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities.

 

Required profile

Experience

Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration
  • Communication
  • Problem Solving

Machine Learning Engineer Related jobs