Proving $(λ^d + (1-λ^d)e^{(d-1)s})^{\frac{1}{1-d}}\leq\sum\limits_{n=0}^\infty\frac1{n!}λ^{\frac{(d^n-1)d}{d-1}+n}s^ne^{-λs}$ Question
Let $\lambda \in (0,1), s \in (0,\infty), d \in \{2,3,\dots\}$ and show that in this case the following inequality holds:
$$(\lambda^d + (1-\lambda^d) e^{(d-1)s})^{\frac{1}{1-d}} \leq \sum_{n=0}^\infty \frac{\lambda^{\frac{(d^n-1)d}{d-1}+n}s^n}{n!} e^{-\lambda s},$$
Thoughts
My first intuition was to try and write the left hand side as some taylor series but this seems like a bad idea as the only part to write as a Taylor series is $e^{(d-1)s}$ and if we "ignore" the $\lambda^d$ this part is what gives $e^{-s}$ which is bounded by $e^{-\lambda s}$.
Maybe there is some formula for a convex expression of the form $\lambda^d a + (1-\lambda^d) b$ which can be used here? Applying convexity I can write the right hand side as $e^{-(1-\lambda^d)s}$ which, unfortunately, is not smaller than the right hand side (for large values of $s$ the inequality fails, which is logical as convecity inequality is increasingly inaccurate as $s$ increases).
I might be able to show it using the Taylor expansion of $f(x) := \frac{1}{(1+x)^{1/n}}$ as I can write the right hand side as:
$$
(1 + (1-\lambda^d) (e^{(d-1)s}-1))^{1/(1-d)},
$$
for this I can take the taylor series at $0$ for $|x|=|(1-\lambda^d) (e^{(d-1)s}-1)| < 1$ and at $\infty$ for $|x| > 1$.
It seems to me that I need something like the binomial approximation but for large values of $x$ rather than small values of $x$.
Promising technique
I can write the left hand side as 
$$e^{-s} (1 + \lambda^d (e^{(1-d)s} - 1))^{1/(1-d)}$$
as $|\lambda^d (1-e^{(1-d)s})| < 1$ we can use the Taylor expansion of $1/(1+x)$ at $0$. This allows us to reduce the inequality to showing:
$$
e^{-s} \sum_{n=0}^{\infty} \frac{1}{n!} \frac{\Gamma(1 - 1/(d-1))}{\Gamma(1 - 1/(d-1) - n)} \cdot \lambda^{nd} (e^{(1-d)s}-1)^n
\leq 
\sum_{n=0}^{\infty} \frac{\lambda^{((d^n-1)d)/(d-1)+n}s^n}{n!}e^{-\lambda s}.
$$
The separate terms in the sum on the right hand side drops to zero much faster than the sum on the left hand side, but the first couple of terms of the right hand side are a lot larger than those on the left hand side. It seems to me that this corresponds to the fact that the Taylor series on the left hand side converges very slowly to the function, maybe we can take a better Taylor series which converges faster.
 A: Too long for a comment (but I can delete it if you want) so :
In fact the RHS is a polynomial more particulary a Jensen polynomial :
Why? Because the coefficients fulfill the conditions also called Turan's inequality:
$$\sigma_k^2\geq \sigma_{k-1}\sigma_{k+1}$$
Proof (here $\lambda=\sigma$):
We have to prove :
$$\sigma^{2\frac{d^n-1}{d-1}+2n}\geq \sigma^{\frac{d^{n-1}-1}{d-1}+n-1}\sigma^{\frac{d^{n+1}-1}{d-1}+n+1}$$
After simplification we have :
$$\sigma^{2\frac{d^n-1}{d-1}}\geq\sigma^{\frac{d^{n-1}-1}{d-1}}\sigma^{\frac{d^{n+1}-1}{d-1}}$$
We take the logarithm on each side we get :
$${2\frac{d^n-1}{d-1}}ln(\sigma)\geq\frac{d^{n-1}-1}{d-1}ln(\sigma)+\frac{d^{n+1}-1}{d-1}ln(\sigma)$$
The logaritm is negative so we reverse the inequality :
$${2(\frac{d^n-1}{d-1})}\leq\frac{d^{n-1}-1}{d-1}+\frac{d^{n+1}-1}{d-1}$$
Finally we get :
$$2\leq \frac{1}{d}+d$$
Wich is obvious 
So it's a serious way to prove it but now I have not the time to conclude
Edit :
The associated polynomials to Jensen polynomials are :
$$g_n(t)=\sum_{k=0}^{n}{n\choose k}\sigma_tx^t$$
Futhermore we know (let $g_n(t)=g_n(t)(\phi;x)$) then the polynomials $g_n(t)$ are generated by  :
$$e^t\phi(xt)=\sum_{k=0}^{\infty}g_n(x)\frac{t^n}{n!}$$
Theorem A from this link asserts this :
the function $\phi(x)$ belongs to L-P if and only if all the polynomials $g_n(\phi;x)$,$n=1,2,\cdots$ have only real zeros .  
From this link we can say that the zeros of Jensen polynomials are simple and negative so we can express the Jensen polynomials like this :
$$f(z)=cz^me^{-\alpha z^2+\beta z }\prod_{n=0}^{\infty}(1-\frac{z}{z_n})e^{\frac{z}{z_n}}$$
So the infinite sum becomes a product... maybe it could help .
