Sr Data Scientist (Causal ML)

Description

JOB TITLE:    Causal Machine Learning Data Scientist

Syneos Health is the only fully integrated biopharmaceutical solutions organization purpose-built to accelerate customer success. We lead with a product development mindset, seamlessly connecting our capabilities to add high-value insights to speed therapies to patients and provide practical value to help our customers achieve their objectives.

Every day we perform better because of how we work together, as one team, each the best at what we do. We bring many talented experts together across a wide range of business-critical services that support our business. Every role within Corporate is vital to furthering our vision of Shortening the Distance from Lab to Life®.

Discover what our 30,000 employees, across 110 countries already know: WORK HERE MATTERS EVERYWHERE

Why Syneos Health

• #SyneosHealthLife means we’re committed to our Total Self-culture – where everyone can authentically be themselves. Our Total Self-culture is what unites us globally, and we know every person’s unique contributions make a difference.
• We believe our success is a direct result of the people who are driving it – you! We value your dedication to caring for our customers and patients, so we want to focus on taking care of you. That’s why we offer a comprehensive benefits program encompassing your total health - physical, mental, and financial.
• We are continuously building the company we all want to work for and our customers want to work with. Why? Because when we bring together diversity of thoughts, backgrounds, cultures, and perspectives – we’re able to create a place where everyone feels like they belong.

JOB SUMMARY

We are looking to recruit a skilled Causal Machine Learning Data Scientist at Syneos Health. This role focuses on using causal inference techniques to unearth actionable insights from complex data, which will drive informed decision-making across our organization. Your expertise will be instrumental in developing robust models that not only predict outcomes but also clearly delineate the causal relationships that underpin these predictions. This is a unique opportunity for someone who is passionate about pushing the boundaries of traditional analytics and applying sophisticated causal analysis to real-world problems.

JOB RESPONSIBILITIES

- Design and implement statistical models to identify and quantify causal effects, enhancing our understanding of the key drivers behind business outcomes.

- Collaborate with stakeholders to formulate relevant business questions that can be addressed through causal analysis, translating complex data into actionable strategies.

- Develop and deploy machine learning algorithms that integrate causal inference, ensuring that models are both accurate and interpretable.

- Conduct robustness checks and sensitivity analyses to validate the assumptions and stability of causal models.

- Stay updated with the latest research and advancements in causal inference and machine learning, integrating innovative methods and tools into our data science practices.

- Communicate findings and methodologies effectively to both technical and non-technical audiences, ensuring that insights drive strategic business decisions.

Qualifications

QUALIFICATION REQUIREMENTS 

- A Master’s degree or PhD in Statistics, Data Science, Economics, or a related field, with a strong focus on causal inference or related methods.

- Demonstrated experience in applying causal inference techniques in a business or research setting, with a portfolio of projects that showcase your ability to extract and communicate causal insights.

- Proficiency in programming languages such as Python, with extensive experience using libraries and frameworks that support causal analysis (e.g., DoWhy, CausalML).

- A strong analytical mindset with the ability to tackle complex problems, test hypotheses, and handle data ambiguities.

- Excellent communication skills, with the capability to articulate the value of causal insights to enhance business strategies.

- Experience with machine learning techniques and their application in building predictive models.

Tech Stack:

- Python

- Causal inference libraries (e.g., DoWhy, CausalML)

- Machine Learning frameworks (scikit-learn, PyTorch)

- Data visualization tools (matplotlib, seaborn)

- MS Azure

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. The benefits for this position include a company car or car allowance, Health benefits to include Medical, Dental and Vision, Company match 401k, eligibility to participate in Employee Stock Purchase Plan, Eligibility to earn commissions/bonus based on company and individual performance, and flexible paid time off (PTO) and sick time.  Because certain states and municipalities have regulated paid sick time requirements, eligibility for paid sick time may vary depending on where you work. Syneos complies with all applicable federal, state, and municipal paid sick time requirements.

The annual base salary (US Only) for this position ranges from $102,600 to $178,600.  The base salary range represents the anticipated low and high of the Syneos Health range for this position.  Actual salary will vary based on various factors such as the candidate’s qualifications, skills, competencies, and proficiency for the role.

Get to know Syneos HealthOver the past 5 years, we have worked with 94% of all Novel FDA Approved Drugs, 95% of EMA Authorized Products and over 200 Studies across 73,000 Sites and 675,000+ Trial patients.

No matter what your role is, you’ll take the initiative and challenge the status quo with us in a highly competitive and ever-changing environment. Learn more about Syneos Health.

Additional Information:Tasks, duties, and responsibilities as listed in this job description are not exhaustive.  The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities.  Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description.  The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above.   Further, nothing contained herein should be construed to create an employment contract.  Occasionally, required skills/experiences for jobs are expressed in brief terms.  Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees.  The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.

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